Social media fact checking method and system

ABSTRACT

A fact checking system verifies the correctness of information and/or characterizes the information by comparing the information with one or more sources. The fact checking system automatically monitors, processes, fact checks information and indicates a status of the information.

CROSS-REFERENCE TO RELATED APPLICATION(S)

This application is a continuation application of co-pending U.S. patentapplication Ser. No. 13/528,563, filed on Jun. 20, 2012, and titled“FACT CHECKING METHOD AND SYSTEM” which is a continuation application ofU.S. Pat. No. 8,229,795, filed on Apr. 17, 2012, and titled “FACTCHECKING METHODS” which is a continuation application of U.S. Pat. No.8,185,448, filed on Nov. 2, 2011, and titled “FACT CHECKING METHOD ANDSYSTEM” which claims the benefit of U.S. Provisional Patent ApplicationSer. No. 61/495,776, filed Jun. 10, 2011, and titled “FACT CHECKINGMETHOD AND SYSTEM,” all of which are hereby incorporated by reference intheir entireties for all purposes.

FIELD OF THE INVENTION

The present invention relates to the field of information analysis. Morespecifically, the present invention relates to the field ofautomatically verifying the factual correctness of a statement.

BACKGROUND OF THE INVENTION

Information is easily dispersed through the Internet, television andmany other outlets. One major problem is that the information dispersedis often not correct. Although there are fact checking websitesavailable online, these websites check facts in a slow manner; typicallynot truly providing a fact check response for several hours or evendays.

SUMMARY OF THE INVENTION

A fact checking system verifies the correctness of information and/orcharacterizes the information by comparing the information with one ormore sources. The fact checking system automatically monitors,processes, fact checks information and indicates a status of theinformation.

The fact checking system includes many embodiments, some of which aresummarized herein. The fact checking system is able to be used toprovide supplemental information, for example, information regarding acommunication, information about a person or other entity,advertisements, opposing advertisements, information about a user,information about an item, media analysis, commercial analysis, biasclassification, a follow-up question for a host, arguments and opposingarguments, and information based on the importance to a user.

The fact checking system is able to be implemented using rated sources,classified sources, a recognition system, learning, contextdetermination, auto-correction, parallel computing and/or many otherfeatures.

The fact checking system will provide users with vastly increasedknowledge, limit the dissemination of misleading or incorrectinformation, provide increased revenue streams for content providers,increase advertising opportunities, and support many other advantages.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates a flowchart of a method of implementing fact checkingaccording to some embodiments of the present invention.

FIG. 2 illustrates a block diagram of various implementations of factchecking according to some embodiments.

FIG. 3 illustrates exemplary screenshots of various implementations offact checking according to some embodiments.

FIG. 4 illustrates a block diagram of an exemplary computing deviceconfigured to implement fact checking according to some embodiments.

FIG. 5 illustrates a diagram of a network of devices configured toimplement fact checking according to some embodiments.

FIG. 6 illustrates exemplary implementations according to someembodiments.

FIG. 7 illustrates exemplary source ordering according to someembodiments.

FIG. 8 illustrates an example of providing supplemental informationbased on information from a television where the supplementalinformation is displayed on a user's mobile device according to someembodiments.

FIG. 9 illustrates a flowchart of a method of providing additional orsupplemental information according to some embodiments.

FIG. 10 illustrates an exemplary table of arguments and counterarguments according to some embodiments.

FIG. 11 illustrates an exemplary table of brands according to someembodiments.

FIG. 12 illustrates an exemplary data structure implementing selectionsand advertising according to some embodiments.

FIG. 13 illustrates an exemplary listing of headlines with an importancerating according to some embodiments.

FIG. 14 illustrates a flowchart of a method of determining an importanceof information according to some embodiments.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT

A fact checking system verifies the correctness or accuracy ofinformation by comparing the information with one or more sources.Although the phrase “fact checking” is used, any sort of informationanalysis is to be understood (e.g. determining a phrase is “spin” orsarcasm).

Monitoring

The fact checking system monitors any information including, but notlimited to, text, video, audio, verbal communications or any other formof communication. Communications include, but are not limited to email,word processing documents, Twitter (tweets), message boards, web pagesincluding, but not limited to, Facebook® postings and web logs, anycomputing device communication, telephone calls, television audio, videoor text, other text, radio, television broadcasts/shows, radiobroadcasts, face-to-face conversations, VoIP calls (e.g. Skype™), videoconferencing, live speech and any other communication that is able to beanalyzed. In some embodiments, monitoring includes recording, scanningor any other type of monitoring. In some embodiments, monitoring alsoincludes capturing and/or transmitting the data. In some embodiments,monitoring includes determining if a portion of the information is factcheckable.

Processing

To perform fact checking, the monitored information is processedincluding, but not limited to, transmitted, converted, parsed,formatted, analyzed and reconfigured using context determination and/orany other processing. For example, voice data is converted to text,screen text is converted to usable text, graphics are converted to ausable form of data, or any other data conversion is able to beimplemented to enable fact checking. For some types of monitoredinformation, little, if any, processing is performed. For example, textwhich is already properly formatted is able to be fact checked withoutany conversion. In another example, when comparing audio to searchableaudio records conversion may not be needed. In some embodiments,processing also includes capturing and/or transmitting the data.Formatting is able to include changing the order of words deletingunnecessary words and/or any other formatting to enable the informationto be searched.

Verification/Fact Checking

The information including, but not limited to, phrases, segments,numbers, words, comments, values, graphics or any other data is analyzedor verified using the fact checking system. In some embodiments, aphrase is first located or determined, and then it is analyzed. Theverification or fact checking process compares the data to be verifiedwith data from one or more sources. In some embodiments, the sources areweb pages on the Internet, one or more databases, one or more datastores and/or any other source. In some embodiments, the source is apersonal source including, but not limited to, an online log or diary.

In some embodiments, the data verification or fact checking is astraight text comparison, and in some embodiments, anotherimplementation including, but not limited to, natural language,context/contextual comparison or intelligent comparison is used. In someembodiments, a combination of search implementations is used.

An example of a straight text comparison is comparing the phrase, “Texasis the largest state” with text to find “Texas is the largest state.”When the text is not found because Alaska is the largest state, a resultof false is returned. An example of a context comparison is: “Texas isthe largest state” where a list of states by size is found, and Texas islocated in the list; when Texas is not #1, a result of false isreturned, or the location in the list is returned, e.g. #2. In anotherexample of context comparison: “Texas is the largest state,” the landmass of Texas is compared with land masses of the other 49 states, andsince Texas does not have the largest land mass, the result is false. Anexample of an intelligent comparison is: X criticizes Y because Y had anaffair, then the intelligent comparison locates a story that indicates Xhad an affair two years ago. An indication of hypocrisy by X ispresented.

In some embodiments, previously checked facts are stored (e.g. in adatabase on a server) to prevent the perpetration of a false statementor story, or other characterization. In some embodiments, the facts arefirst checked manually or automatically which is able to occur inreal-time or non-real-time, but then when a repeat occurrence happens,the results of that fact check occurs in real-time. For example, a storythat Candidate X is a communist is presented by one commentator. Thestory is fact checked, and the result of the fact check (e.g. not true)is stored, including the original comment and any context related. Then,when another commentator or anyone else says, “Candidate X is acommunist,” the fact checker uses the previously stored result toimmediately inform a viewer/user that the story is not true. Thus,commentators and others will not bother perpetuating a false story asthey will not only be proven wrong immediately but will also damagetheir credibility.

In some embodiments, the sources are rated using a rating system so thatsources that provide false or inaccurate information are rated as pooror unreliable and/or are not used, and sources that rarely providemisinformation are rated as reliable and are used and/or given moreweight than others. For example, if a source's rating falls or is belowa threshold, that source is not used in fact checking. In someembodiments, users are able to designate the threshold. For example, auser specifies to fact check using only sources with an “A” rating orhigher. In some embodiments, sources' ratings are available or shown tousers. In some embodiments, users are able to rate sources. In someembodiments, sources are rated based on previous fact checking resultsto determine computer-generated ratings. For example, if a source isproven wrong by comparing the data with other sources or the resultswith other sources' results, that source would be rated as poor. Forfurther example, Source X indicates that Z is true, but twenty otherreliable sources indicate that Z is false. Such a result would affectSource X's reliability rating negatively. Examples of very reliablesources include a dictionary and an encyclopedia. An example of apotentially very unreliable source includes a biased, opinion web logthat fabricates stories. In some embodiments, an impartial group ororganization rates the sources, or any other method of rating thesources is used. In some embodiments, sources are reviewed by an agency(e.g. an independent rating agency) to obtain a reliability rating. Insome embodiments, a combination of user ratings, computer ratings and/orother ratings is implemented. In some embodiments, there are separateclasses of ratings or reviews including, but not limited to, generalusers, experts, friends, co-workers, news organizations or any othergroups. The rating system is able to be numeric including, but notlimited to, 1-10, by grades including, but not limited to A-F or anyother rating or grading system. Furthermore, the rating system is ableto be incorporated into a mathematical equation to provide higherquality results. For example, if a statement is being verified, and twodifferent sets of results are found such that one set of resultsverifies the statement as fact and the other set verifies the statementas fiction, the one from the higher rated sources is selected. A sampleequation is:

Source Result Value=Number of Sources*Average Rating of Sources, wherethe search path with highest Source Result Value determines theverification result. For example, “Person X is running for president,”results in 10 sources with an average rating of 9 (where 1 isuntrustworthy and 10 is very trustworthy) saying “True,” and 20 sourceswith an average rating of 2 saying “False,” the result would be “True”since (10*9)=90 is greater than (20*2)=40. Another sample equation is:Source Result Value=(Source Rating1+Source Rating2+ . . . SourceRatingn)/number of sources.

In some embodiments, the sources are classified in one or moreclassifications including, but not limited to, comedy, opinion, fact,fiction, and/or political. Any other classifications, groupings,sub-classifications, and/or sub-groupings are possible. In someembodiments, sources are rated in political terms including, but notlimited to, independent, ultra-liberal, leaning left, neutral/moderate,leaning right, ultra-conservative, green, and libertarian.

In some embodiments, a user is able to customize which sources are usedand/or not used. For example, if a user believes Source Z providesinaccurate information, the user is able to mark that source so that itis not used. In some embodiments, sources are clustered, so that a useris able to select a cluster instead of individual sources. For example,a user is able to select to use all dictionary and encyclopedicreferences. In some embodiments, a user is able to select sources basedon characteristics including, but not limited to, a politicalcharacterization (e.g. conservative). Any other user selection orexclusion of sources is possible.

In some embodiments, a phrase to be fact checked may not have an exactanswer, the answer may not be known at the time, or the fact checkingsystem may not be able to find the answer. If this occurs, a “bestguess” is able to be selected and presented. In some embodiments, eachresult from a source that is checked is able to include a resultaccuracy rating. For example, if a fact to be checked is, “the U.S. has50 states,” many sources should return a 100% accuracy rating for theresult since it is easily searched for and determined within thesources. However, if a fact to be checked is not easily determined, theresults may be less than 100% accurate and could therefore be labeled asa “best guess” including a confidence/accuracy/certainty percentage,instead of a fact.

In some embodiments, for example, where the facts are not certain, acollective determination system is used. For example, a determinationthat 40 sources (e.g. sites) agree with the statement and 5 disagree,allows the user to make a judgment call and look further into thestatement.

In some embodiments, where a subjective statement is made or asked,ratings, objective information, and/or subjective information is locatedto determine the accuracy of the statement or question. For example, ifa person says, “Star Wars is better than Star Trek,” ratings informationgiving Star Wars an 8.5 and Star Trek and 8.0 would verify the validityof the statement, and the fact checker would return the statement“True.” The ratings information is able to be any ratings informationincluding, but not limited to, user ratings, critic ratings, otherratings or a combination thereof. In some embodiments, if an opinion isdetected (e.g. by recognizing, “in my opinion,” “I think” or anotheropinion phrase), the statement is not ruled as valid or invalid, butsupporting information is able to be detected and presented (e.g. 10sites agree with your opinion and 5 disagree). In some embodiments, ifan opinion without basis/justification is detected, an indication of“unfounded opinion” is indicated or the basis is presented. In someembodiments, pros and cons of each are provided so that the user is ableto make the determination of which is better. In some embodiments, whena user submits a subjective item, one or more results are presented thatanswer the subjective item. For example, if a user searches using asearch engine for “the best restaurant in San Francisco,” a singlerestaurant is presented which has the highest rating for restaurants inSan Francisco. In some embodiments, since there are several ratingagencies/sites, multiple restaurants are presented, and a descriptionsuch as “highest rated by X” is presented next to each result. Forexample, Restaurant X is highest rated by source A, Restaurant Y ishighest rated by source B and Restaurant Z is highest rated by source C.In some embodiments, all of the rating agencies/sites are compared, anda single entity is presented. For example, if there are 10 sites thatrate songs, and 8 agree that Song J is the best ever, while 2 agree thatSong L is the best ever, Song J is presented as the best song ever. Insome embodiments, users are able to select how they want the resultspresented including, one ultimate result, a list of results, a graph ofresults, and/or any other presentation.

In some embodiments, context determination is used such that the contextof the comment is checked in determining the validity of the comment.For example, if someone says, “he wasted billions of dollars,” the “he”is determined based on additional context surrounding the statement. Inanother example, the question is also analyzed to determine if theresponse is valid. For instance, if a question asks, “Did you receiveany money illegally?,” and a respondent answers, “I have not beenconvicted of a crime,” that comment is able to be flagged as “spin,”“unresponsive,” “questionable” or the like, since technically the answerto the question is true, but the point of the question has not reallybeen answered. Other forms of context checking are able to beimplemented as well to provide more information to the viewer. In someembodiments, when “spin,” a nonresponsive response or any sort ofquestionable response is detected, a host is notified, so that he isable to press the issue. For example, a television show host asks aguest if the guest has ever “cheated on his taxes,” and the guestresponds with, “I have never been convicted of tax fraud.” A yellowlight is displayed to signal the host to ask the question in a differentmanner or further press the issue to try to get to the truth. Asdescribed herein, in some embodiments, an additional question isautomatically presented (e.g. on a teleprompter or in his earpiece), sothat the host does not have to formulate the additional question. Insome embodiments, a follow-up question is presented to the host afterevery response by the guest. In some embodiments, the question is basedon the guest's answer.

Context is able to be used in many ways to find an answer. For example,if Person A says Person B is biased, there may not be an exact statementto be found that says, “Person B is biased.” However, using context,biased quotes, pictures, stories, audio, video or other data may befound from Person B which would indicate he is biased. Additionally,when there may be a gray area such as someone being biased, both sidesare able to be found and presented for the viewer to determine thetruth. For example, audio with Person B denigrating a specific groupwould indicate bias, but video of that same person helping that specificgroup would indicate non-bias or a change of view.

In some embodiments, hyperbole, sarcasm, comedy and other linguisticstyles are checked and/or detected, and the information is indicated assuch. Detection occurs using any contextual qualities including, but notlimited to, the tone, the channel/station/type of website (e.g. a newschannel), and/or type of person (e.g. comedian).

In some embodiments, causation is analyzed and fact checked. Forexample, if Z makes the statements, “A is Russian, Russia in the pastwas communist, therefore A is a communist,” an indication that thecausation is weak is presented. Weights of causation are able to beindicated including, but not limited to, weak causation, strongcausation or a number rating including, but not limited to, 1 through10. In some embodiments, causation is able to be analyzed by determininglinks between items, and the greater the number of links and/or theseverity of the links, the greater the causation. Where causation isdifficult to analyze and/or establish, an alert questioning causation isindicated. For example, if a commentator makes the statement that pricesof goods went up in the under President Z, if there is insufficient datato indicate that the prices went up because of actions President Z took,an indication of “questionable causation” is able to be presented. Insome embodiments, causation (or lack thereof) is determined by logicalflaws or incorrectness. For example, if a commentator makes the claimthat President Z harmed businesses by lowering taxes, an indication of“poor causation” is able to be made since it is logically inconsistentfor lowering taxes to harm businesses. In some embodiments, sourcessupporting and/or contradicting the information are displayed. In someembodiments, a list or another description is displayed indicating otherpossible causes for the result. For example, if a commentator says theeconomy is in trouble because of the President, a list of other possiblecauses could be displayed such as Congress, a credit collapse, andothers, including percentages next to each indicating percentages basedon previous polling.

In some embodiments, when the data verification or fact checking occurs,one or more dedicated sources are used. In some embodiments, one or morenon-dedicated sources are used. In some embodiments, a combination ofdedicated and non-dedicated sources is used. In some embodiments, thereliability of the data verification depends on the number of sourcesused. For example, if a story has 5 independent sources that verify thestory, then that would be considered and denoted more reliable than astory with 1 source. The reliability of the sources is also able toaffect the reliability of the story. For example, although 5 sourcesverify a story, if the sources are all poorly rated sources in terms ofreliability, then that story may be considered less reliable than astory that has 1 very reliable source. In some embodiments, animplementation is used to determine if the same story/article is usedmore than once as a source. For example, if there is only one source foran article but the same story is posted on ten different websites, insome embodiments, that repetition is recognized and only counts as oneverification source.

In some embodiments, a user performs a check of the automatic fact checkresults.

In some embodiments, checks are performed to ensure sources or sourcedata are not stale, or that stale sources or source data are not usedwhen fact checking. For example, if the statement, “X is running forPresident” is made regarding the 2016 election, and several sources havedata that show X ran for President in 2000, that data is ignored sinceit does not prove that X is running in the 2016 election. Checking forstale sources and source data is able to be done by comparing a creationdate of the data or other characteristics or landmarks of the sources ordata or any other manner.

In some embodiments, via social networking, contacts' sources' searchresults or other related information is used when performing a user'ssearch. For example, a user fact checks the “Tiger is the best golfer,”and a contact (e.g. friend) had already done this fact check. Theresults from that fact check are given to this user. This is able toimprove search speed and accuracy.

Indicating Status

After fact checking is performed, an indication or alert is used toindicate/inform/alert a user of a status of the information including,but not limited to, correct/true/valid or incorrect/false/invalid. Inaddition to correct and incorrect, other gray area indicators arepossible including, but not limited to, “unknown,” “depending on thecircumstances” or “close to the truth.” Additionally, any other statusindicators are possible. The indicators are able to be any indicatorsincluding, but not limited to, lights, sounds, highlighting, text, atext bubble, a scrolling text, color gradient, headnotes/footnotes, aniconic or graphical representation (e.g. a meter, Pinocchio's nose orthumbs up/down), a video or video clip, music, other visual or audioindicators, a projection, a hologram, a tactile indicator including, butnot limited to, vibrations, an olfactory indicator, a Tweet, an email, apage, a phone call, or any combination thereof. For example, text isable to be highlighted or the text color is able to change based on thevalidity of the text. For example, as a user types, the true statementsare displayed in green, the questionable statements are displayed inyellow and the false statements are displayed in red. Similarly, when acommentator speaks on a television program, true statements aredisplayed in a first color and false statements are displayed in asecond color. Additional colors or shades of color or brightness ofcolors are able to be used to indicate other items including, but notlimited to, hyperbole, opinions, and other items. In some embodiments,sources to the verification data are provided (e.g. using hyperlinks orcitations). In some embodiments, the text itself includes a hyperlink.The source enables the user to verify the statement himself, forexample, by reviewing an original source for an article. In someembodiments, a phrase itself is not affected or labeled, but additionalinformation is provided in close proximity. For example, if a politicianon a talk show says, “the President raised the deficit by $1 T thisyear,” the fact checking system presents data showing the deficit fromlast year and this year, so that users are able to compare what thepolitician said and what an independent source said. In someembodiments, indicating includes transmitting and/or broadcasting theindication to one or more devices (e.g. televisions).

In some embodiments, the fact checking system is implemented such thatresponses, validity determinations and/or indications are available inreal-time or near real-time. By real-time, it is meant instantaneously,for example, such that when a politician makes a comment on a politicalshow, within a second or a few seconds, the comment is fact checked, andan indication of the validity of the comment is presented. Furthermore,since the monitoring, processing, fact checking and indicating are allable to be performed automatically without user intervention, real-timealso means faster than having a human perform the search and presentingresults. Depending on the implementation, in some embodiments, theindication is presented in at most 1 second, at most several seconds(e.g. at most 5 seconds), at most a minute, at most several minutes orby the end of a show. In some embodiments, the time amount (e.g. at most1 second) begins once a user pauses in typing, once a phrase has beencommunicated, once a phrase has been determined, at the end of asentence, once an item is flagged, or another point in a sequence. Forexample, a commentator makes the comment, “Z is running for President.”As soon as that phrase is detected, the fact checker checks the fact,returns a result and displays an indication based on the result in lessthan 1 second—clearly much faster than a human performing a search,analyzing the search results and then typing a result to be displayed ona screen.

FIG. 1 illustrates a flowchart of a method of implementing fact checkingaccording to some embodiments of the present invention.

In the step 100, information is monitored. In some embodiments, allinformation is monitored; in some embodiments, only some information ismonitored; or in some embodiments, only explicitly selected informationis monitored. In some embodiments, although all information ismonitored, only some information (e.g. information deemed to befact-based) is utilized for the fact check analysis. Monitoring is ableto be implemented in any manner including, but not limited to, storingor recording the information, transmitting the information, and anyother method of monitoring. The information to be monitored is anyinformation including, but not limited to, television audio, video ortext, other text, radio, television broadcasts/shows, radio broadcasts,word processing data and/or documents, email, Twitter (tweets), messageboards, web pages including, but not limited to, Facebook® postings andweb logs, any computing device communication, telephone calls,face-to-face conversations, VoIP calls (e.g. Skype™), videoconferencing, live speech and any other information. In someembodiments, monitoring includes, but is not limited to, observing,tracking, collecting, scanning, following, surveying and/or overseeing.

In the step 102, the information is processed. In some embodiments,processing includes converting the information into a searchable format.During or after the information is monitored, the information isconverted into a searchable format. Processing is able to include manyaspects including, but not limited to, converting audio into text,formatting, parsing data, determining context and/or any other aspectthat enables the information to be fact checked. Parsing, for example,includes separating a long speech into separate phrases that are eachseparately fact checked. For example, a speech may include 100 differentfacts that should be separately fact checked. In some embodiments, thestep 102 is able to be skipped if processing is not necessary (e.g. textin word processor may not need to be processed).

In a more specific example of processing, broadcast information isconverted into searchable information (e.g. audio is converted intosearchable text), and then the searchable information is parsed intofact checkable portions (e.g. segments of the searchable text; severalword phrases). Parsing is able to be implemented in any mannerincluding, but not limited to, based on sentence structure (e.g.subject/verb determination), based on punctuation including, but notlimited to, end punctuation of each sentence (e.g. period, questionmark, exclamation point), based on search results and/or any othermanner. In some embodiments, processing includes, but is not limited to,calculating, computing, storing, recognition, speaker recognition,language (word, phrase, sentence, other) recognition, labeling, and/orcharacterizing.

In the step 104, the information is fact checked. Fact checking includescomparing the information to one or more sources of information todetermine the validity, accuracy, quality, character and/or type of theinformation. In some embodiments, the comparison is a straight word forword text comparison. In some embodiments, the comparison is a contextcomparison. In some embodiments, an intelligent comparison isimplemented to perform the fact check. Any method of analyzing thesource information and/or comparing the information to the sourceinformation to analyze and/or characterizing the information is able tobe implemented. An example implementation of fact checking includessearching (e.g. a search engine's search), parsing the results orsearching through the results of the search, comparing the results withthe information to be checked using one or more of the comparisons (e.g.straight text, context or intelligent) and retrieving results based onthe comparison. The results are able to be any type including, but notlimited to, binary, Boolean (True/False), text, numerical or any otherformat. In some embodiments, determining context and/or other aspects ofconverting could be implemented in the step 104. In some embodiments,the sources are rated and/or weighted. Although the phrase “factchecking” is used, any sort of information analysis is to be understood(e.g. determining a phrase is sarcasm).

In the step 106, a status of the information is indicated. The status isindicated in any manner including, but not limited to, transmittingand/or displaying text, highlighting, underlining, color effects, avisual or audible alert or alarm, a graphical representation, and/or anyother indication. The meaning of the status is able to be any meaningincluding, but not limited to, correct, incorrect, valid, true, false,invalid, opinion, hyperbole, sarcasm, hypocritical, comedy, unknown,questionable, suspicious, need more information, deceptive, and/or anyother status. The status is also able to include other informationincluding, but not limited to, statistics, citations and/or quotes.Indicating the status of the information is also able to includeproviding additional information related to the fact checkedinformation. In some embodiments, indicating includes pointing out,showing, displaying, recommending, playing, presenting, announcing,arguing, convincing, signaling, asserting, persuading, demonstrating,denoting, expressing, hinting, illustrating, implying, tagging,labeling, characterizing, and/or revealing.

In some embodiments, fewer or more steps are implemented. Furthermore,in some embodiments, the order of the steps is modified. In someembodiments, the steps are performed on the same device, and in someembodiments, one or more of the steps, or parts of the steps, areseparately performed and/or performed on separate devices.

Example 1

A news channel broadcasts a show with political commentary. The showallows a host and guests to discuss various political issues. As thehost and guests make comments, their comments are monitored, convertedfrom speech to text and automatically fact checked using online datasources. Based on the results of the fact check, a status of thecomments is shown. For example, if the guests respond with factuallyaccurate statements, no alert is displayed. However, when a guest orhost makes an untrue statement, an alert is displayed at the bottom ofthe screen including a quote of the incorrect statement and a correctionto the statement. If a guest “spins” a comment, the fact checker is ableto determine “spin” and indicate “spin” for the comment and provide datathat explains why it is spin. This ensures the guests provide valid dataand arguments, as well as maintains the integrity of the show.

Example 2

A user is typing a report using a word processor. As the user is typing,the word processor monitors the information being input. Depending onthe format of the information, the information may not need to beconverted. The information, such as segments of the report, is factchecked. For example, a user is typing a report on the history of NewJersey and types, “Newark is the capital of New York” The fact checkerwould compare this segment with an online source such as Wikipedia.organd determine that Trenton is the capital of New Jersey. As a result,the word processor would strikethrough “Newark” and next to it, insertTrenton, underlined. Any other means of indicating that the informationis wrong is able to be used. In some embodiments, supplementalinformation and/or citation information is provided. For example,regarding the capital city, information such as Trenton became thecapital in 1790, and the state flower is the Common Violet. In someembodiments, the fact checker is used as a citation finder. For example,if a user types in a statement, regardless of whether it is correct, theuser is able to select the text and click “cite finder” where the factchecker provides sources that verify the statement. The “cite finder” isnot limited to word processing applications and is able to be applied inany implementation.

Example 3

A user posting information to his Facebook® page types commentaryregarding his favorite golfer, and says, “I can't believe Tiger came ineighth this week.” Using additional data such as knowing when thecommentary was written and that the user is an avid golf fan, aftermonitoring this information, converting the information including addingthe context of Tiger Woods (the famous golfer), at the Masters, in 2011,the fact checker is then able to compare this information with theresults of that specific tournament for that specific golfer. Then, ablurb with a citation is able to be posted on the user's Facebook® pageto indicate that Tiger actually finished fourth, or the user is informedso that he is able to correct the page himself.

Example 4

A user searches using a search engine by inputting “Alaska is thelargest state.” The search engine provides a response of True and alsodisplays one or more links to the sources that support the result. Inanother example using the search engine, a user searches using thephrase, “Magic Johnson is taller than Michael Jordan.” The search enginedetermines that Magic Johnson is 6′9″ and Michael Jordan is 6′ 6″ andthen compares the heights with a mathematical operator to provide theresult of True. In some embodiments, the heights of each are displayed,and in some embodiments, one or more cites providing the informationused in the comparison are displayed.

FIG. 2 illustrates a block diagram of various implementations of factchecking according to some embodiments. As described herein, somespecific implementations are shown including, but not limited to, a wordprocessing component 200 for incorporation with a word processingapplication, an advertising component 202 for advertising, an entityvalidity rating component 204 for rating entities, a source ratingcomponent 206 for rating sources, a flagging component 208 for flaggingitems, a voice/facial/biometric recognition component 210 forrecognizing entities, a self-checking component 212 for checking a user,a learning component 214 for learning, an auto-correction component 216for implementing auto-correction, a search engine component 218 forimplementing a search engine fact checker, an audio/video/text component220 for fact checking audio, video, text and any other information, atranslator component 222 for translation-fact checking, a text component224 for fact checking an email, instant message, text messages, tweetsor other text communications, an item determination component 226 fordetermining an item, a media analysis component 228 for analyzing mediaincluding but not limited to, television and radio, a re-broadcastcomponent 230 for applying fact checking analysis to re-broadcastedinformation, a supplemental information component 232 for providingsupplemental information to content, an action component 234 for takingan action against an entity based on the fact checking, an opposingarguments component 236 for providing opposing arguments to content, aparallel component 238 for implementing parallel monitoring, processing,fact checking and/or indicating, an importance rating component 240 fordetermining the importance of content, and a medical fact checkercomponent 242 for fact checking medical information. The variousimplementations shown are not meant to be limiting in any way and aremerely examples of some of the possible implementations.

FIG. 3 illustrates exemplary screenshots of various implementations offact checking according to some embodiments.

Screenshot 300 shows a word processing display where a user typed astatement, the statement has been fact checked, and a notificationappears with a suggestion to correct the incorrect statement. Although abubble with the correction is shown, any form of indicating an errorand/or correction is possible including, but not limited to,underlining, strikethrough, highlighting, an icon, and/or an audiblealert. When there are multiple ways of correcting a statement, a user isable to be given options as described herein.

Screenshot 302 shows a television screen where a commentator is makingstatements. Since the commentator made a false statement, text isdisplayed at the bottom of the screen indicating the statement is falseand providing a correction of the false statement.

Screenshot 304 shows multiple forms of rating speakers on a televisionbroadcast. Statistics for the guest speaker in the window are shownbelow the window indicating the number of true statements he has madeand the number of false statements he has made. A rating is displayedunder the host of +10 which, for example, is a positive rating of +10 ona −10 to +10 truthfulness scale. These ratings enable users to determinehow trustworthy the speaker is based on past results.

Screenshot 306 shows a smart phone which monitored a user's comments andinformed him that he misspoke by saying the U.S. has 51 states.

Screenshot 308 shows a search engine search and result. In the example,the user searches for the fact, “Texas is the largest state.” The resultpresented is “False,” a correction is shown, and citations (links) ofsupporting websites or other sources are shown. In another the example,the user searches for the fact, “Alaska is the largest state.” Theresult presented is “True” and citations (links) of supporting websitesor other sources are shown. The displayed results are able to vary fromsimple (e.g. merely presenting True or False) to more detailed (e.g.presenting True or False, providing a correction if false, providingspecific information, and providing citations).

The various implementations illustrated in FIG. 3 are not meant to belimiting in any way and are merely examples of some of the possibleimplementations.

FIG. 4 illustrates a block diagram of an exemplary computing device 400configured to implement the fact checking method according to someembodiments. The computing device 400 is able to be used to acquire,store, compute, process, communicate and/or display informationincluding, but not limited to, text, images, videos and audio. In someexamples, the computing device 400 is able to be used to monitorinformation, process the information, fact check the information and/orindicate a status of the information. In general, a hardware structuresuitable for implementing the computing device 400 includes a networkinterface 402, a memory 404, a processor 406, I/O device(s) 408, a bus410 and a storage device 412. The choice of processor is not critical aslong as a suitable processor with sufficient speed is chosen. The memory404 is able to be any conventional computer memory known in the art. Thestorage device 412 is able to include a hard drive, CDROM, CDRW, DVD,DVDRW, flash memory card, solid state drive or any other storage device.The computing device 400 is able to include one or more networkinterfaces 402. An example of a network interface includes a networkcard connected to an Ethernet or other type of LAN. The I/O device(s)408 are able to include one or more of the following: keyboard, mouse,monitor, display, printer, modem, touchscreen, touchpad,speaker/microphone, voice input device, button interface, hand-waving,body-motion capture, touchless 3D input, joystick, remote control,brain-computer interface/direct neural interface/brain-machineinterface, and other devices. In some embodiments, the hardwarestructure includes multiple processors and other hardware to performparallel processing. Fact checking application(s) 430 used to performthe monitoring, converting, fact checking and indicating are likely tobe stored in the storage device 412 and memory 404 and processed asapplications are typically processed. More or less components shown inFIG. 4 are able to be included in the computing device 400. In someembodiments, fact checking hardware 420 is included. Although thecomputing device 400 in FIG. 4 includes applications 430 and hardware420 for implementing the fact checking, the fact checking method is ableto be implemented on a computing device in hardware, firmware, softwareor any combination thereof. For example, in some embodiments, the factchecking applications 430 are programmed in a memory and executed usinga processor. In another example, in some embodiments, the fact checkinghardware 420 is programmed hardware logic including gates specificallydesigned to implement the method.

In some embodiments, the fact checking application(s) 430 includeseveral applications and/or modules. Modules include a monitoring modulefor monitoring information, a processing module for processing (e.g.converting) information, a fact checking module for fact checkinginformation and an indication module for indicating a status of theinformation. In some embodiments, modules include one or moresub-modules as well. In some embodiments, fewer or additional modulesare able to be included. In some embodiments, the applications and/orthe modules are located on different devices. For example, a deviceperforms monitoring, converting and fact checking but the indicating isperformed on a different device, or in another example, the monitoringand converting occurs on a first device, the fact checking occurs on asecond device and the indicating occurs on a third device. Anyconfiguration of where the applications/modules are located is able tobe implemented such that the fact checking system is executed.

Examples of suitable computing devices include, but are not limited to apersonal computer, a laptop computer, a computer workstation, a server,a mainframe computer, a handheld computer, a personal digital assistant,a pager, a telephone, a fax machine, a cellular/mobile telephone, asmart appliance, a gaming console, a digital camera, a digitalcamcorder, a camera phone, a smart phone/device (e.g. a Droid® or aniPhone®), an iPod®, a tablet (e.g. an iPad®), a video player, ane-reader (e.g. Kindle™), a DVD writer/player, a Blu-ray® writer/player,a television, a copy machine, a scanner, a car stereo, a stereo, asatellite, a DVR (e.g. TiVo®), a home entertainment system or any othersuitable computing device.

FIG. 5 illustrates a network of devices configured to implement factchecking according to some embodiments. The network of devices 500 isable to include any number of devices and any various devices including,but not limited to, a computing device (e.g. a tablet) 502, a television504, a smart device 506 (e.g. a smart phone) and a source 508 (e.g. adatabase) coupled through a network 510 (e.g. the Internet). The sourcedevice 508 is able to be any device containing a source including, butnot limited to, a searchable database, web pages, transcripts,statistics, historical information, or any other information or devicethat provides information. The network 510 is able to any network ornetworks including, but not limited to, the Internet, an intranet, aLAN/WAN/MAN, wireless, wired, Ethernet, satellite, a combination ofnetworks, or any other implementation of communicating. The devices areable to communicate with each other through the network 510 or directlyto each other. One or more of the devices is able to be an end user, amedia organization, a company and/or another entity. In someembodiments, peer-to-peer sourcing is implemented. For example, thesource of the data to be compared with is not on a localized source butis found on peer sources.

For example, a news company uses its computers to monitor and processinformation presented on its broadcast. The processed information isthen fact checked with one or more sources (on site and/or external),and then the results are presented to the user's home device such as atelevision. The monitoring, processing, fact checking and presenting areall able to occur locally at the news company, externally by anotherentity, or parts occur locally and parts occur externally. In a modifiedexample, the results are sent to and presented to a user on hercomputer, smart phone or tablet while she is watching television.

In another example, when a user is watching television, the user's smartphone monitors and processes information from the television and sendsthe information to be fact checked, and then the results are presentedon the user's smart phone.

In another example, when a user is watching television, the user'scomputing device monitors and processes information from the televisionand sends the information to be fact checked, and then the results arepresented on the user's computing device.

In another example, when a user is watching television, the user's smartphone monitors and processes information from the television and sendsthe information to be fact checked, and then the results are sent fromthe user's smart phone to the television to be presented.

Any combination of devices performing the fact checking system ispossible.

Implementations

Advertising

In some embodiments, advertising is incorporated with the fact checkingsystem. For example, a fact checking result includes, “This fact checkis brought to you by: Company X.” In some embodiments, the advertisingis related to the item being checked or the result of the fact check.For example, if the fact to be checked is “California is the mostpopulated state,” an advertisement about California is presented. Insome embodiments, the advertising is based on other information insteadof or in addition to the fact to be checked including, but not limitedto, a user's age, sex, location, occupation, industry of the fact,location of a subject, or any other information. In some embodiments,personal networking information is used including, but not limited to,Facebook® information. In some embodiments, coupons are presented withthe fact checking. For example, if a fact to be checked is whether “IceCream Z is gluten-free,” a coupon for Brand Z ice cream is presented tothe user. Another example is pay per click or click-throughmoney-making. Any other implementation of making money using the factchecking system is able to be implemented. FIG. 6 illustrates exemplaryimplementations including an advertisement 600. Additional advertisingimplementations are described herein, for example, in the SupplementalInformation section.

Entity Validity Rating and Recognition

In some embodiments, an entity including, but not limited to, a speaker,author or another entity (e.g. corporation) has a validity rating thatis included with the distribution of information from him/it (forexample, see FIG. 3, screenshot 304). For example, if a politician hasbeen found to have misstated the truth, an indication of such is able tobe displayed when he appears on a television program. In anotherexample, when a commentator appears, statistics of how many factuallyaccurate statements have been made by him and/or factually inaccuratestatements have been made by him are presented during the show. In someembodiments, parameters related to the statistics are able to beselected (e.g. specific to a show or a time period). In someembodiments, a running tally is presented throughout the show. Theindication is able to include any information including, but not limitedto, statistics, highlighting, the other indications described hereinand/or any indication to further inform the audience of histrustworthiness. In the example further, text appears on the televisionscreen, such as at the bottom, which states, Senator A has misstated thetruth 10 times, but has been truthful 20 times. The severity of themisstatement is also able to be factored in when rating a person orentity. For example, stating that something occurs 90% of the time butin reality it occurs 89% of the time is a minor and possible ignorablemistake. However, stating something occurs 90% of the time when itoccurs 20% of the time is not likely a rounding error or a slip of thetongue. Additionally, the subject of the mistake is also able to betaken into account in terms of severity. For example, if a person makesan untrue statement about the country of origin of baseball, that is aminor mistake, whereas making an untrue statement about tax informationis a major mistake, and the major mistake is weighted more than theminor mistake. In some embodiments, an independent agency determineswhat is major and what is minor. In some embodiments, individual usersare able to indicate what is important to them and what is not. In someembodiments, another implementation of determining what is major, minorand in between is implemented. The context of the situation/statement isalso able to be taken into account. In some embodiments, entities areable to fix their validity rating if they apologize for or correct amistake, although measures are able to be taken to prevent abuses ofapologies. Another specific form of indication includes gradients ofcoloring such that a truthful person is highlighted with a border inbright green, and the green becomes less bright as the truthfulness ofthe person decreases and becomes red when they are viewed as less thantruthful, ultimately reaching bright red when considered completelyuntruthful. Any combination of colors is able to be used, or any otherindication described herein is able to be used. In some embodiments, inaddition to or instead of a validity rating, an entity is able toinclude another rating, including, but not limited to, a comedic ratingor a political rating. In some embodiments, an entity includes aclassification including, but not limited to, political, comedy oropinion. Examples of information or statistics presented when an entityappears include, but are not limited to the number of lies,misstatements, truthful statements, hypocritical statements or actions,questionable statements, spin, or any other characterizations. In someembodiments, the information or statistics are available through a link,mouse-over, picture-in-picture or other implementation. In someembodiments, specifics of the statements are able to be viewed; forexample, by clicking on “hypocritical statements,” a list of thehypocritical statements is presented to the user. In some embodiments,both the hypocritical statement and the source statement are shown. Insome embodiments, the source for one or both of the statements is shown.Additional statistical information is available too, including, but notlimited to, the severity of the statement (e.g. egregious lie versusminor mistake). In some embodiments, users are able to specify an amountof statements shown: by number of statements, by time period ofstatements (e.g. last 6 months) or by any other implementation. Forexample, Person X's last 5 hypocritical statements (out of 30) areshown. In some embodiments, dates or time frames are used in determiningthe relevance of fact check comparison. For example, if a hypocriticalstatement was made 30 years ago, the fact checker may realize that itwas more likely a change of view rather than a hypocritical statement;whereas, a contradictory statement made 2 weeks ago is likely due tohypocrisy not a change of view. In some embodiments, friends, familymembers, co-workers, users and others have validity ratings.

In some embodiments, the entity rating is implemented using a databaseor other data structure. For example, the database includes a column orrow with names and their corresponding entity rating. In embodimentswhere additional information is stored, additional column(s) includespecific information such as hypocritical statements, severity of themistakes, and any other information. The database is then used to lookup the entity's information for indicating the information.

In some embodiments, people/face recognition is implemented. Forexample, a politician is on a talk show, and the face recognitionidentifies the politician. Once recognized, information about thepolitician is displayed including, but not limited to, the validityrating described herein, statistics, and/or other information. In someembodiments, the information posted includes quotes of most outrageousthings said, most truthful things said, or other specific quotes.Similarly, other recognition is able to be implemented including, butnot limited to, voice recognition or biometric recognition. For example,a mobile application recognizes who is talking by voice recognition andposts a validity rating and/or other information on the phone. In otherexamples, at a dinner party the mobile application is able to identify aperson who tells tall tales, or at a negotiation, the application isable to indicate if the opposing side is honest. Voice recognition isalso able to identify someone on a television show or radio show. Insome embodiments, users' online/screen/usernames are identified. In someembodiments, a person's identity is input by a user, and theninformation is displayed about that person. FIG. 6 illustrates exemplaryimplementations including facial/people recognition 602.

In some embodiments, when an entity is displayed (e.g. on a devicescreen), the entity's positions on topics are displayed. For example,political positions are displayed (e.g. pro-life, pro-choice, anti-tax,others). The positions are able to be regarding a lighter material thanpolitical positions such as personal preferences regarding foods,entertainment and any other information. In some embodiments, differentmagnitudes regarding the positions are able to be displayed. Forexample, if someone is a fervent anti-war activist, the person's fervoris indicated. In some embodiments, evidence is provided showing theentity's position. For example, a voting record is shown to indicatethat the person may be saying she is against raising taxes, but voted 10times to raise taxes while in Congress. FIG. 6 illustrates exemplaryimplementations including entity information 604.

Flagging

In some embodiments, users are able to flag statements. FIG. 6illustrates exemplary implementations including flagging information606, where highlighting text is shown. Users are able to flag thestatements using Twitter, polling, text messaging (e.g. SMS or MMS),audio texts, video texts, phone, voice, selecting (e.g. with a mouse,keyboard, remote control, hand-waving, body-motion capture, touchless 3Dinput or joystick), highlighting, copying, or any other implementationof flagging a statement. In some embodiments, a flagged statement isthen highlighted or another effect is applied. Flagging is also able toinclude a “thumbs up”/“thumbs down” or “happy face”/“frown”representation, for example, users who feel the statement is valid wouldgive a “thumbs up.” Although the word “flag” is used, the strictdefinition is not implied. Any form of highlighting, pointing out,commenting on, selecting, or linking to is able to be implemented.Comments are able to be flagged as valid/true, invalid/untrue,questionable, unverifiable, depending (on context) or using a scaleincluding, but not limited to, 1-10, where 1 is blatantly false and 10is definitely true. Comments are also able to be flagged as spin,comedy, sarcasm, hyperbole, hypocritical and/or any othercharacterization. Comments are able to be flagged to force them to befact checked (e.g. manually forced fact checking). Additionally,comments are able to include support for the flag, including, but notlimited to, a citation supporting or proving the user's position. Insome embodiments, the users who flag statements are rated. For example,the users are rated by comparing their flagging with results of a factcheck. In some embodiments, if a user is wrong often, then his flag isnot used. In some embodiments, if a user's rating is or falls below athreshold, the user is ignored. In some embodiments, separate classes ofusers are implemented for flagging, including, but not limited to,media, viewer, and professional. In some embodiments, if a user iscorrect often, his flag is used and is able to have a stronger value. Insome embodiments, a weighting scheme is used such that a value of auser's flag is proportional to the correctness of previous flags. Forexample, if User A flags 100 items as wrong, and after a fact check, theuser is found to have wrongly flagged 95 items, that user's future flagswill have little weight or will possibly be ignored; whereas, if User Bflags 100 items as wrong, and after a fact check, the user is found tohave correctly flagged 95 items, that user's future flags will haveweight and possibly additional weight compared to others. In someembodiments, a competition is implemented using flagging where users areasked to assess the validity of statements, and the user who is correctthe most often wins the competition. Any other competitions involvedwith fact checking are possible as well.

Structure, Execution and Sources

In some embodiments, a site is specifically designed (e.g. formatted)for data verification or fact analysis. For example, common quotesand/or data are appropriately formatted to be compared with other text,speech or any other communication. In an example, speech checking occurssuch that if a commentator says, “Person A said X, Y and Z,” a digitalversion of the transcript would be located and compared to determine ifPerson A actually said X, Y and Z.

In some embodiments, the fact checking system has the ability to learn.The learning is able to be in terms of context, detecting items likesarcasm, cheating or manipulation of data sources and other items thatwould help the fact checking process. In some embodiments, a database isused to track people's comment habits or history and other information.For example, if Person X is known for using hyperbole, the fact checkingsystem is able to recognize that and then provide future indicationsusing such knowledge. In some embodiments, new sources are able to befound using learning. For example, a crawler, data miner, bot, and/orother implementation is able to search for and utilize additionalsources of information for fact checking. Learning is also able toinclude analyzing archived data of sources to determine the reliabilityof the sources. In some embodiments, if a characterization or other itemhas not been learned, an expandable list of options is presented to auser for the user to select an option.

In some embodiments, an auto-correction feature is implemented. Forexample, if text is being monitored, when a factual statement isinaccurate, the text is automatically changed. In some embodiments, theuser is asked if they want to correct the statement. In someembodiments, the flawed text is merely indicated including, but notlimited to, underlined, highlighted or change in font/color. In someembodiments, in video, the auto-correction feature automatically poststext on the video with the correction.

In some embodiments, specific phrases known to be true or false areadded to a database and/or a website, so that the fact checking systemis able to indicate the correctness of the phrase. For example, if onenews organization is known for misquoting someone and continuing to usethe misquote instead of the correct quote, that is able to bedetermined, and the quote is indicated as incorrect. In someembodiments, the correct quote is displayed or is accessible (e.g.through a hyperlink).

In some embodiments, determining which phrases to be fact checked isperformed automatically (e.g. by a computing device). In someembodiments, determining which phrases to be fact checked is performedmanually. For example, while a television broadcast is occurring, one ormore individuals select segments of the broadcast to be fact checked. Asa further example, if a person says, “we need to do something abouttaxes, unemployment is at 10%,” the first part of that sentence probablydoes not need to be fact checked or is labeled an opinion, but“unemployment is at 10%” is an easily verifiable fact. In someembodiments, manual and automatic fact checking are implementedtogether. For example, a user selects a sentence to be fact checked outof a paragraph, but a device automatically parses the sentence forseparate phrases to be fact checked.

In some embodiments, information is checked for being stale or outdated.For example, if a news organization runs a story that occurred manymonths ago but presents the story as occurring recently, the factchecking system is able to alert the user by presenting a date of whenthe story initially occurred. Determining if the information is stale isable to be performed in any manner including, but not limited to, a datecomparison. In some embodiments, fact checking is updated as informationchanges. For example, saying X is running for President may be labeledas “uncertain” at one point, but then when X officially declares that heis running, the label is changed to “true.”

In some embodiments, the source of the information to be checked and/orthe organization presenting the information to be checked are related toand/or are working in cooperation with the fact checking system. Forexample, a news organization implements its own fact checking system topresent results to viewers. In some embodiments, the source of theinformation to be checked and/or the organization presenting theinformation to be checked are unrelated to and/or are not working incooperation with the fact checking system. For example, a companyindependent from the news organization implements the fact checkingsystem on a user's mobile device so that when the mobile device receivesinformation from the news organization, the mobile device performs thefact checking.

In some embodiments, caching is implemented to speed up the factchecking process. Caching is able to be implemented in any manner. In anexample, if Commentator X is known to spread the same lie, that specificlie is not re-checked; rather, when that lie is made, an indication thatthe statement is a lie is presented based on cached analysis of thestatement. In some embodiments, cached data is re-checked periodicallyto ensure the data does not become stale. In some embodiments, there-checking occurs in the background to avoid interruption of any otherprocessing.

Any search algorithm, sorting algorithm, data structure and/or otherdata organizational or analysis scheme is able to be used to implementthe fact checking system and any other systems described herein. Forexample, advanced search algorithms, advanced search text algorithms,indexing and searching by indices, including combinations of searchimplementations, are able to be used. Data structures including, but notlimited to, arrays, queues, maps, buffers, tables, matrices, lists,trees, heaps, graphs, classes and subclasses, databases, and otherstructures, including combinations of data structures are able to beused. The search, sorting, data structure and/or other dataorganizational or analysis scheme is able to be used in any aspect ofthe fact checking system including, but not limited to, locatingsources, organizing sources, comparing information with sourceinformation, searching within sources, storing sources and any otheraspect. In another example, a data structure is used for implementingthe fact checker and/or providing supplemental information by storingrelationships and/or related items, including, but not limited to,arguments/opposing arguments, misquotes/correct quotes,brands/competitors, and/or any other items.

In some embodiments, pattern recognition of recognizing a pattern isimplemented in any aspect of the fact checking system. For example, thepattern recognition is implemented in monitoring information. In anotherexample, the pattern recognition is implemented in processing theinformation. In another example, pattern recognition is implemented infact checking including, but not limited to, locating sources,organizing sources, comparing information with source information,searching within sources, storing sources and any other aspect.

In some embodiments, a queue or other structure is implemented to storefacts or other items to be checked when a connection is not available.

In some embodiments, sources are rated based on popularity or“trending.” For example, if Site X has 1,000,000 individual hits perday, and Site Z has 50 individual hits per day, Site X has a higherpopularity. Popularity is able to be established using any methodincluding, but not limited to, total hits per time frame, unique hitsper time frame, quantity of links to the source, quality of linkingitems to the source, duration of existence of the source, any othermethod and/or any combination thereof. Any of the sorting, filtering andapplying of thresholds described regarding reliability ratings andsources is able to be applied to popularity and sources. For example,the fact checker is able to be limited to sources with a popularityabove a specified threshold. In some embodiments, both popularity andreliability are implemented in determining which sources to use. In someembodiments, other reliability determinations are used with thepopularity rating to determine the reliability of a source.

In some embodiments, the sources are ordered by reliability (forexample, as shown in FIG. 7), and when information is fact checked, theprocess of fact checking starts the search with the most reliable sourceand continues to less reliable sources. In some embodiments, a structuresuch as a tree, list or any other structure includes pointers to thesources ordered by reliability. In some embodiments, the order isdescending order from most reliable to least reliable. In someembodiments, the order is ascending order from least reliable to mostreliable. In some embodiments, the order is configurable. In someembodiments, a fact checking search stops after N (e.g. N=2) sourcesverify the fact.

A short version of an exemplary list of sources ordered by reliabilityincludes:

1. a link to the Random House Dictionary website with a reliabilityrating of 100% reliability,

2. a link to the Britannica Online Encyclopedia website with areliability rating of 100% reliability,

3. a link to the XYZ News website, with a 90% reliability, and

4. a link to Bob's made-up-opinion-on-all-things website, with a 1%reliability.

In some embodiments, multilevel fact checking is implemented. Forexample, a phrase is fact checked, but before the fact check iscompleted, the source is fact checked to determine if the source isreliable. The multilevel fact checking is able to continue until areliable source is found, and then the fact check of the phrase iscompleted with the reliable source.

In some embodiments, sources are classified as fact/objective andopinion/subjective. For example, a data structure such as a tree isimplemented with objective sources on one side of the tree andsubjective sources on the other side of the tree. In another example, asone goes left to right at the bottom of the tree, the sources go frommost objective to most subjective. The sources are able to be classifiedby determining what the majority of their content is, by beingclassified by a user, by including a classification tag, or any othermethod.

In some embodiments, a determination of whether information is taken outof context is made. The determination is made by comparing the audio,video, text and/or other content used with the original or full version.For example, if a news organization shows a clip (e.g. portion of avideo), the entire video is made available to a user for a period oftime before and/or after of the clip is shown. For example, 30 secondsof the video before the clip started is shown.

In some embodiments, the data verification or fact checking occurs on aremote server including, but not limited to, a central server. Theresults are able to be cached and/or sent to users' local machines. Insome embodiments, the data verification or fact checking occurs at auser's local machine. In some embodiments, the data verification or factchecking occurs using cloud computing.

The fact checking system is able to be implemented on a separate devicethat couples or communicates with a television; as part of a television,radio or Internet broadcast or any other broadcast; on a mobile deviceincluding, but not limited to, an iPhone® or Droid®; on a computer; on atablet including, but not limited to, an iPad®; or any other device.

In some embodiments, the fact checking system is a smartphoneapplication including, but not limited to, an iPhone®, Droid® orBlackberry® application. In some embodiments, a broadcaster performs thefact checking. In some embodiments, a user's television performs thefact checking. In some embodiments, a user's mobile device performs thefact checking and causes (e.g. sends) the results to be displayed on theuser's television and/or another device. In some embodiments, thetelevision sends the fact checking result to a smart phone.

In some embodiments, parallel monitoring, processing, fact checkingand/or indicating is implemented. For example, two or moreimplementations of a fact checker are used. In the example, the two ormore implementations are able to be on the same device or on differentdevices. In a further example, each implementation is different, andthen the results of each are compared to determine a “best” resultand/or to provide several results. For example, one implementation of afact checker excludes certain sources, while another fact checker usesall sources, and their results are able to be different, and in someembodiments, the different results are presented to a user and/orratings are provided with the results and/or other information isprovided. In some embodiments, monitoring and processing are implementedin parallel with fact checking. For example, one device monitors andprocesses information and a second device performs the fact checkingwhile the monitoring and processing occurs. In some embodiments,pipelining is implemented. In some embodiments, distributed processingis implemented. For example, multiple devices perform fact checking(e.g. searching, comparing and returning results) and return a compositeresult. In some embodiments, separate fact checkers are implemented tofact check multiple data providers (e.g. broadcasters, newspapers,websites and/or any other communications/information). In someembodiments, the fact checking multiple data providers occurs at thesame time, and in some embodiments, the fact checking occurs atdifferent times. For example, 3 fact checkers are implemented to factcheck 3 major cable news networks. In some embodiments, one fact checkeris able to fact check multiple data providers at the same time. Whenfact checking multiple data providers, the information from each is ableto be shared, compared, and/or any other processing/analysis is able tobe performed. For example, if 5 out of 6 data providers lead with StoryA, but the 6th data provider leads with Story B, an indication is ableto be made that Story B is presenting different information. In someembodiments, multiple fact checkers are used to fact check differentaspects of a show. For example, a first fact checker is used to factcheck historical information, a second fact checker is used to factcheck charts and graphics, and a third fact checker is used to providesupplemental information.

Supplemental Information

FIG. 8 illustrates an example of providing supplemental informationbased on information from a television 800 where the supplementalinformation is displayed on a user's mobile device 802. In someembodiments, the fact checking system provides clarifying comments oradditional (or supplemental) information to assist a user or viewer. Forexample, if a commentator makes a general statement that the cost of acleanup will cost X dollars, the fact checking system is able to findspecifics regarding the cost and provide a detailed explanation of eachcomponent of the total cost.

FIG. 9 illustrates a flowchart of a method of providing additional orsupplemental information according to some embodiments. In the step 900,information is monitored. For example, broadcast information (e.g. atelevision program or advertisement) is monitored. In the step 902, theinformation is processed. For example, the information is parsed. In thestep 904, additional or supplemental information is searched for andreturned. For example, a database is searched to find opposing argumentsto an argument, or supporting arguments are searched for on web pages,or a competitor's advertisement is located in a database, or any othersupplemental information is found and returned. The amount ofinformation returned depends on the implementation. For example, a linkto a webpage could be returned, a link to a video, the video itself,text, and/or any other information is returned. In the step 906, thesupplemental information is indicated or displayed. For example, anopposing argument is displayed on a mobile device. As described herein,monitoring, processing, searching and indicating are able to beimplemented in many different ways and are able to include manydifferent items.

In some embodiments, supplemental information is provided withoutperforming the step of fact checking. For example, monitoring,processing and indicating still occur, but instead of fact checking,supplemental information is found and returned. As an example, a newsshow is monitored, processed (e.g. converted and parsed), and thensupplemental information is determined (e.g. located) and indicated. Forexample, a person discusses a new candidate from North Dakota, NorthDakota is searched for and is found in an encyclopedic source, some orall of the encyclopedic information is retrieved, and supplementalinformation providing statistics about North Dakota is shown. In anotherexample, a person states, “the U.S. debt has been growing significantlyunder this President;” supplemental information is able to be displayedshowing U.S. debt growth under some or all of the previous Presidents.In another example, if a complex issue is discussed, clarification isprovided. For instance, if a complex economic issue is discussed, theissue is broken down into simpler parts. In yet another example, ifsomething is explained incorrectly or not clearly, clarification isprovided. For example, during the Presidential race, national polls aredisplayed regularly; however, national polls mean very little due to theElectoral College election system of the U.S. Therefore, supplementalinformation providing battleground state polling is able to be shown tosupplement the national polls. In some embodiments, supplementalinformation is provided for both sides of an argument. Any of the othersteps and implementations described herein are applicable to providesupplemental information without fact checking.

In some embodiments, supplemental information includes an advertisement.In some embodiments, a price comparison is displayed. In anotherexample, a viewer is watching an awards show and on the red carpet,celebrities are wearing designer brands of attire, and an advertisementfor each dress/suit/shoe/clothing/jewelry/items is displayed (or asimilar knock-off item is displayed). In some embodiments, thesupplemental information is presented on the same device the user iswatching (e.g. television). In some embodiments, the supplementalinformation is presented on a separate device such as mobile deviceand/or another device. In some embodiments, the supplemental informationis a Tweet, an email, a text message and/or any other communication. Insome embodiments, the advertisement is presented during the programbeing viewed, and in some embodiments, the advertisement is presentedafter the program is viewed.

In some embodiments, supplemental information is provided based on aheadline, title, caption, talking point and/or other short phrase. Forexample, titles (or any other short phrases) are monitored, processed,fact checked and a result is indicated. In some embodiments, the step offact checking is replaced with finding supplemental information. Byfocusing on just the title, less processing takes place. For example, ifa news program begins the show with “Nasdaq Hammered,” statisticalinformation of the worst days for the Nasdaq are indicated for the user.In another example, if a headline states, “Taxes Going Up,” supplementalinformation that specifies which taxes are going up, by how much andwhen the taxes are going up is indicated. Or in some instances, rebuttalsupplemental information that indicates taxes are not going up (e.g. ifthe information is outdated or new information showing taxes are notgoing up) is presented. The amount of supplemental information is ableto be as short as a single word (e.g. False!) or as detailed as a 200+page study or anywhere in between and including any kind of informationto provide the user with more information. In some embodiments, analysisof only the title (or other heading) is used for an opposing view to bepresented. For example, if a headline states, “Global Warming CausingWildfires,” supplemental information of an opposing view that discusseshow the wildfires are caused by La Niña is presented.

Supplemental information is found and returned in any manner, including,but not limited to, the same or similar manner(s) described regardingfact checking. For example, information is searched for by comparing theinformation with sources, and information related to the searched forinformation is returned. In another example, the supplementalinformation is stored in a data structure such as a database or table.

In some embodiments, one or more opposing arguments are indicated inresponse to content or information. In some embodiments, the opposingarguments are based on fact checking information. In some embodiments,the opposing arguments are indicated without fact checking theinformation; rather, opposing arguments are determined and presented.For example, an argument is determined, the argument is classified, anopposing argument is determined, and then the argument is presented. Insome embodiments, a table (or other data structure) contains argumentsand matching opposing arguments. In some embodiments, the opposingargument or supplemental information is based on politicalclassification. In some embodiments, a set of links of arguments arecoupled with opposing arguments. For example, a pro-life argument isdetected, which finds that argument in the table, and then thecounter-argument coupled with the argument is found. FIG. 10 illustratesan exemplary table of arguments and counter-arguments according to someembodiments. Sub-arguments and sub-counter-arguments are also able to beincluded. In another example, if a person makes a comment with aposition, an opposing position is indicated without fact checking theposition. To further the example, if a guest on a political show makes acomment, an opposing position is indicated on the television screen intext. Indicating the opposing position is able to be in any manner asdescribed herein (e.g. text on a television screen or text on a mobiledevice). In some embodiments, determining the opposing argument is ableto be based on keywords detected, based on the speaker/author/entity ofthe position, based on political leanings of the speaker/author/entity,based on context, based on metadata, and/or based on any other detectiondescribed herein. For example, if a keyword of “abortion” is detected,and the speaker is a strict conservative, a description of a liberalview is presented. In another example, if keywords of “President” and“economy” are detected by a liberal commentator, context is able to beused such as the current date to determine which President is beingdiscussed, and economic data, past and present, including comparisons,is able to be presented to the user. Such additional information wouldhelp guarantee a balanced presentation of information to users.

In some embodiments, an opposing advertisement is presented when anadvertisement is presented. For example, if there is a commercial forBeer X displayed on the television, a commercial for Beer Y is displayedon the user's mobile device, on a smaller section of the television(e.g. bottom of the screen), or another device. FIG. 11 illustrates anexemplary table with Brand X and Brand Y, where when a Brand Xcommercial is detected, a Brand Y commercial is displayed on the user'sdevice, or vice versa. In some embodiments, a fee scheme is implementedwith this to collect advertising money from Brand Y. In someembodiments, multiple companies/products are included within the table(e.g. Brand X, Brand Y and Brand Z), and when one is detected one ormore of the others is displayed (e.g. in a random manner, in analternating manner, based on advertising fees by the brands, or in anyother manner). In another example, when an advertisement for a newmedicine is detected, supplemental information providing the sideeffects and other negatives is displayed. In another example, anopposing political advertisement is displayed. In some embodiments, thegroupings of the arguments or commercials/products/companies aregenerated automatically (e.g. based on searches), and in someembodiments a user inputs groupings, or both are implemented. In anotherexample, an advertisement for Candidate X is displayed, and anadvertisement for Candidate Y is displayed on the same device or anotherdevice. In some embodiments, a correction or contradiction to anadvertisement is displayed. For example, an advertisement says,Candidate X raised taxes N times, and a correction and/or advertisementexplains Candidate X never raised taxes. As described herein, anautomatic rebuttal is able to be implemented. For example, if CandidateX knows of the advertisements run by Candidate Y which attack CandidateX, Candidate X is able to generate advertisements that directly refutethe attacks which are then run at the same time or in response to theCandidate Y advertisements (for example, using a table similar to FIG.11 where Candidate X and Candidate Y are in the same row of the table oranother form of linking) In some embodiments, the original content (e.g.advertisement) and the opposing content are displayed on the samedevice, and in some embodiments, the original content and the opposingcontent are displayed on different devices (e.g. original on television,opposing on mobile device or vice versa). As described herein, in someembodiments, a commercial or advertisement is detected based on aproduct, a company and/or language in the commercial/advertisement,metadata, or any other method. For example, an advertisement for SodaBrand X by XYZ Corp. is detected based on monitoring for “Soda Brand X,”“XYZ Corp.” and/or a catch-phrase or other language used incommercial/advertisement. In some embodiments, acommercial/advertisement is detected using another implementation.

In some embodiments, opposing arguments are presented by an opposingentity including, but not limited to, a website, televisioncompany/network/station, person, company and/or other entity.Information is able to be monitored, processed, compared with/searchedfor (e.g. in a lookup table or database) and then the opposing argumentis presented. For example, a first entity is able to fact check and/orrespond to another entity with the first entity's analysis (possiblybiased analysis). The first entity makes selections of how to factcheck, analyze and/or respond. The selections include but are notlimited to the site/station/network/show to analyze, keywords orarguments to look out for, responses to arguments, sources to use,styles of responses, format of output, and/or any other selections. Forexample, a conservative blogger selects a liberal news organization tomonitor, specifically indicates to automatically monitor for “globalwarming” and indicates a set of links to books and articles to bedisplayed that present an opposing view of global warming. Then, when aviewer is watching programs from that organization, any time globalwarming is discussed, the viewer is presented the set of links. In someembodiments, the arguments and opposing arguments are stored in a datastructure such as a table. In some embodiments, the selections aregrouped by political classification (e.g. liberal, conservative or anyothers) and/or grouped by other classifications, for example, so theuser only has to select his political classification without specifyingother details. In some embodiments, a user makes selections (e.g.specifying that he is a conservative), and in some embodiments, theselection is automatic. The automatic selection is able to be based onanalysis of websites the user visits (e.g. browser history shows he goesto liberal websites, so automatically select liberal), based onpurchases the user makes (e.g. buys “green” products, so automaticallyselect liberal), based on television/radio shows watched/listened to(watches conservative talk show, so automatically select conservative),and/or any other automatic selection. In some embodiments, a database orother data structure is used to classify and store the websitenames/links, television shows, and any other information. In someembodiments, a user's selection is automatically generated based onsocial networking information such as associations (e.g. if Facebook®friends are conservative, assume user is conservative). In someembodiments, users are able to make several selections to furtherspecify their orientations (e.g. selecting: socially liberal, fiscallyconservative, and environmental). The selections are able to be verybroad, very specific, somewhere in between, and are able to be manyselections or a single selection.

In some embodiments, advertising is presented based on a user'sselection(s) and/or classification(s). In some embodiments, advertisingis presented based on the monitored language. For example, if a user isindicated as liberal and a global warming topic is monitored, a Priusadvertisement is presented. Additional information regarding the user isalso able to be incorporated in determining the advertisement to bepresented. For example, if the user is a new mom and liberal, and anenvironmental topic is presented, an advertisement for “green” diapersis presented. FIG. 12 illustrates an exemplary data structure (e.g. adatabase or a table) implementing selections and advertising. In theexample, user selections/information, keywords to monitor andadvertisements are maintained, as well as any other relevantinformation. Further in the example, user information includes that theuser is a liberal and an environmentalist, therefore the keyword/phrase“Global Warming” is monitored for, and when detected, an advertisementfor a Hybrid X Vehicle is displayed. In some embodiments, recent searchhistory of the user is also included in the data structure.

In some embodiments, supplemental information is indicated forentertainment shows. For example, if a television show is about teenpregnancies, then educational videos, images, links, statistics, games,advertisements, or any other information is indicated. The supplementalinformation is able to be found using any implementation such as by thesearching and comparison described herein including searching a datastructure (e.g. a database) which stores the information to be presentedin response to the entertainment information. In another example, if theshow appears to glorify teen pregnancies, information regarding thenegatives of teen pregnancy is presented. Similarly, if a televisionnetwork is promoting purchasing housing or even “flipping” housing,negatives of owning housing or the dangers of “flipping” housing arepresented. In some embodiments, specific details about the “flipped”house are shown, for example, the purchase price, the expenses, and thesales price. For sports shows, statistics and/or other information isshown. For example, if a user is watching a football game on televisionor on his mobile device, and the game is in the fourth quarter, and thequarterback just threw a completion, additional information is presentedon the user's television or mobile device which shows statistics (e.g.game statistics, historical statistics, other statistics, personalinformation, other information) of the quarterback. For example, toincrease the viewing audience, the personal information could beinformation that would interest a person not interested in footballitself, including, but not limited to, the player's girlfriend, age,alma mater, home town, likes/dislikes, and other information to enticeother viewers to watch. In some embodiments, the supplementalinformation explains the sport/game including, but not limited to, whatjust happened, why there was a penalty, the rules of the sport/game(e.g. how to play Texas Hold'em), the purpose of the sport/game and/orany other explanation to help the audience. In some embodiments, thesupplemental information provides an easy way to purchase items. Forexample, a football jersey advertisement is presented for the jersey ofthe player who just had an exciting play. The way to purchase theitem(s) could be a link to a store to purchase the items, a singlebutton purchase or any other way of providing sales. The supplementalsales information could be related to a commercial or advertisement. Forexample, if a commercial is displayed for X Brand mountain bikes, then astore locator is displayed on a user's device indicating where topurchase the X Brand mountain bike, or an online site with a link topurchase the item (e.g. bike) is presented. In some embodiments, when amovie is being played, related movies are presented or informationincluding, but not limited to, a description, rental information, andpurchase information is presented. In some embodiments, if a movie orother item is referenced in another movie, television show, or othercontent, a clip, transcript or other information of the movie or otherreferred item such as a book or a poem is presented. For example, whenGeorge sings “Master of the House” from Les Miserables in “Seinfeld,” aclip of the musical is shown or lyrics are displayed on the user'sdevice.

In some embodiments, the supplemental information is related to sportsbetting/play-along including, but not limited to, fantasy football andcollege basketball brackets, where a user's fantasy team or bracket isupdated automatically in sync with the game results. For example, if abasketball game ends, the user's bracket is automatically updated andpresented on the user's device including the current standings. Inanother example, as the football games occur, a player's fantasy teaminformation is updated during the games and presented on the user'sdevice.

In some embodiments, news, weather, traffic and/or other information isfact checked by comparing the information with other stations' results(e.g. fact checking by comparison with peers is performed). For example,if News Company A states Candidate X paid $0 in taxes last year, butNews Company B, News Company C and News Company D all say, Candidate Xpaid $100,000 in taxes, the additional information is presented to theuser. In another example, if meteorologist at Channel A says it will be80 degrees today, but meteorologists at Channels B through D and onlinesites Y and Z say it will be 90 degrees today, the additionalinformation is presented to the user. In some embodiments, if a story(e.g. news story) is incomplete on one station, or another station hassupplemental information, that information is presented to the user. Forexample, if one station does not indicate the victim's race, but anotherstation does provide this information, that supplemental information ispresented (e.g. as text at the bottom of the screen with credit given tothe providing source). Determination of the missing information is ableto be by comparing keywords in the information, processing andformatting the information (e.g. by searching for specific items in astory and determining if any information is missing) or any otherimplementation. For example, for a news story about a homicide, a datastructure contains elements for race of the attacker and victim, age ofthe attacker and victim, motive, location, weapon, and any otherinformation. And if any of the information is unknown from onechannel/site/network, other sources of information are able to be usedto fill in the missing information.

In some embodiments, supplemental information is provided by the samesource that is providing the original content (e.g. XYZ Networkbroadcasts a political show and also provides supplemental information).In some embodiments, supplemental information is provided by a thirdparty (or independent party). For example, XYZ Network broadcasts apolitical show, and TTT App provides supplemental information to bedisplayed with the political show, where TTT App has no affiliation withXYZ Network.

In some embodiments, supplemental information is provided when the factchecker is used for print articles. For example, after a user acquirescontent of an article in a magazine, supplemental information related tothe article is provided including, but not limited to, where to buy anitem in the article, what the latest study says about the content of thearticle, and any other information.

In some embodiments, a running log of supplemental information is kept.In some embodiments, the running log is user-specific and/ordevice-specific. For example, the supplemental information for Bob isbased on what Bob has been viewing, reading and/or receiving. In someembodiments, by keeping a log of the supplemental information, repeatedindication of supplemental information is avoided. For example, if aviewer of a television show has already been provided with supplementalinformation about a character, that supplemental information is notautomatically shown again. In an additional example, a data structurestores information indicating what supplemental information has beendisplayed to a specific user, and then that information is used todetermine what supplemental information to display, if any. In someembodiments, updated supplemental information is shown based on theprevious supplemental information. For example, if character informationhas previously been shown to a user, but there is new information sincethe user missed a week, only the new information is shown. In someembodiments, a history of supplemental information is kept, so that theuser is able to search and/or look through this information on demand.

In some embodiments, when numbers or charts are described in words (e.g.in a broadcast), supplemental graphics are displayed. In someembodiments, when a trend or statistics are mentioned, graphics aredisplayed to show the trend. For example, a reporter says, “housingprices have decreased for 5 months,” and then supplemental informationis shown that includes a chart of the past 5 months of housing prices byretrieving 5 months of data and generating a chart using a chartgeneration application. Providing the supplemental information isperformed in any manner; for example, by finding the data and generatinga chart and/or finding the chart. In some embodiments, context is used;for example, if the comment is “over the past 6 months,” then today'sdate is used to find data going back 6 months.

In some embodiments, supplemental information is generated in advance ofa broadcast based on a guest list for the show or other knowledge of theshow. For example, the guest information such as views, biases,political party and/or any other information is able to be located andprepared beforehand for a political guest. Or for an actor appearing ona late night show, recent movies, events in the personal life of anactor, or other information is prepared in advance. In some embodiments,the advanced generation of information is performed automatically, andin some embodiments, the advanced generation of information is performedmanually.

In some embodiments, supplemental information is based on personalconditions, personal traits, recent events and/or other information. Insome embodiments, the information is able to be taken from a socialnetworking site (e.g. Facebook®) or a site/implementation such asTwitter. For example, if a user indicates his mood on a socialnetworking site, that information is able to be used in providingsupplemental information. In some embodiments, the supplementalinformation is used in generating a suggested list of channels and/orprograms for the user. For example, if the user indicated “depressed,” alist of comedies is presented to the user. In another example, if theuser indicated “depressed” and “conservative,” comedies with aconservative slant are presented (or at least presented first in adescending order starting with the most conservative). The supplementalinformation is able to be used in presenting advertisements to the userin combination with or without other elements described herein. In someembodiments, the information (e.g. mood) is fact checked.

In some embodiments, when a word or phrase is mentioned (e.g. in amovie, on the news, in a television show, in person, in a discussion, onthe Web and/or elsewhere), supplemental information is providedregarding that word or phrase. In some embodiments, only words orphrases that are included in a data structure (e.g. database) to providesupplemental information are used. In some embodiments, common phrases(e.g. don't look a gift horse in the mouth) are used. In someembodiments, only words and phrases deemed to be “not well known” areused. For example, if a movie makes a reference to an obscure object orperson, supplemental information is provided so that the userunderstands what or who that object or person is. As described herein,the word or phrase is able to be searched for in a data structure, theweb and/or any other source, and the result of the source is returned(e.g. a definition of the word).

In some embodiments, a data structure, for example a database, a tableor any other data structure, is used to search for and presentsupplemental information. In some embodiments, supplemental informationis based on subsequent searches.

Importance/Relevance

In some embodiments, broadcast information, stories, articles, or othercontent is rated and/or classified in relation to a user. FIG. 13illustrates an exemplary listing of headlines with an importance ratingaccording to some embodiments. In some embodiments, the content is ratedbased on an importance or relevance to the user's life or based on theuser's interests. In some embodiments, the importance is selected by theuser, and in some embodiments, the importance is based on standards of agroup of people (e.g. neighborhood, town, state, country) such ascommunity standards. For example, a community may establish the economyas the most important topic, followed by national security, then taxes,and other items following. In some embodiments, a combination ofcommunity standards and user selections is used to determine importance.Thus, content focused on lower priority (less important) items is ratedlower than higher priority (more important) items. In some embodiments,content is presented to users based on the ratings (e.g. higher ratedarticles are presented at the top of a list to a user). In someembodiments, content that falls below a threshold is not presented to auser. In some embodiments, the user sets the threshold and/or specifieswhich kind of content not to show. For example, articles aboutPresidential wardrobes are not displayed to users where the user'simportance ratings have such content below the user's threshold. In someembodiments, users are able to search based on the importance rating. Inan example of a user-specified rating, a user selects lifestyle choicesas the most important topic followed by the environment. In someembodiments, user-specified ratings are based on social networking siteinformation, search information, preferences, favorites, city or stateof residence, and/or other selections. For example, if a user searchesfor economic data often, then the economy is designated as an importanttopic for the user. In some embodiments, content is rated using multipletopics. For example, an article is rated as to how religious it is, howeconomic-related it is and how environmentally-conscious it is. In someembodiments, the rating in relation to importance to a user is used incombination with other ratings to provide a more complete rating. Forexample, an article is rated highly (e.g. 10) in importance because itinvolves unemployment and creating jobs, but it is rated poorly (e.g. 4)for its lack of accuracy, so the combined rating is a 7 on a scale of 1to 10. In some embodiments, the separate ratings are presentedseparately (e.g. article is a 10 for importance and a 4 for accuracy).Any rating indication is able to be used (e.g. 1-10, A-F, a rainbowgradient of colors, or any other indication). In some embodiments,classification of content is determined based on keywords found withinthe content and/or any other classification. For example, if an articleuses economic terms such as unemployment, stimulus, and taxes, thearticle is able to be classified as related to the economy. In someembodiments, content is able to be classified in one or moreclassifications. In some embodiments, the rating and/or classificationof content is performed by monitoring, processing, keyword searching,and indicating. Keyword searching includes searching within the contentfor keywords. In some embodiments, monitoring or processing includeskeyword searching and/or detection. In some embodiments, the ratingand/or classification is performed automatically. In some embodiments,the rating and/or classification includes fact checking, and in someembodiments, fact checking is not performed. In some embodiments, thereare classifications and one or more levels of sub-classifications. Forexample, a news broadcast that uses the terms: “unemployment,” “stocks,”and “taxes” is able to be included in the class “economy” and thesubclasses “stock market” and “employment.” The importance rating isindicated next to a title, displayed at the beginning of a televisionprogram, displayed in the information of a television program guide,displayed on a mobile device, and/or any other indication. In someembodiments, the classifications are based on general topics including,but not limited to, politics, sports, entertainment, finance and others.For example, if a user has no interest in sports, the user is able toplace that at the bottom of the importance list. Using the sportsexample, “sports” could be the overall classification with specificsports (e.g. hockey, baseball, basketball, football, golf) assub-classifications, and NCAA® football and NFL® football as a furtherlevel of sub-classification. In some embodiments, the position of thearticle (e.g. pro/anti) affects the importance to a user.

In some embodiments, a likelihood of importance is indicated to a userand/or used to determine the importance of an article, where thelikelihood is based on the percentage of the population the articleaffects. In some embodiments, the position of the article (e.g.pro/anti) affects the likelihood of importance. In some embodiments,importance is based on what is trending now (e.g. what people aresearching for, texting about, and/or other popularity based data).

In some embodiments, importance to a user automatically increases ordecreases depending on the number of content (e.g. articles andtelevision shows) presented to and/or selected by the user. For example,a user selects many “economics” articles; therefore, they are likelyimportant to a user, thus the importance rating increases with time. Inanother example, a user has seen 10 television clips about the royalwedding, and the importance rating decreases with time since the user islikely tiring of the story.

In an example of an importance rating being implemented, a websitedisplays titles of 20 articles. The user viewing the website hasselected taxes, environment and foreign affairs as most important to theuser. Three of the articles are rated as 100s (scale of 1 to 100) on theimportance scale since they are focused on taxes (e.g. tax-relatedkeywords are detected), 5 are rated as 99s since they are focused on theenvironment and 1 article is rated a 98 since it is focused on foreignaffairs. The remaining articles fall below the user's threshold, and aregrayed-out or not shown, so that the user is able to focus on articlesimportant to him.

FIG. 14 illustrates a flowchart of a method of determining an importanceof information according to some embodiments. In the step 1400,information (e.g. an article) is analyzed. For example, keywords aresearched for in an article. To further the example, keywords arecompared with a database that classifies the keywords. For example, adatabase specifies that “global warming” is in an environment class, and“gun control” is in a constitutional class or a 2nd amendment class. Inthe step 1402, the information is then classified based on the analysis.For example, an article which uses the words or phrases, “pollution” and“global warming,” is classified as “environmental.” In some embodiments,information is classified in multiple classes. For example, if anarticle discusses guns and the environment, the article is classified ina “guns” classification and an “environment” classification. In someembodiments, the information is classified in only one classification,based on the most relevant classification. For example, if an articlecontains 10 keywords related to war and only 2 keywords related to theenvironment, the article is classified in a “war” classification. Insome embodiments, the classification includes a strength rating. Forexample, the percentage of occurrences, number of occurrences and/oranother analysis is used to determine how strongly the article isclassified. Furthering the example, an article is 90% composed ofkeywords related to war, thus, the article is given a “strong” rating ofbeing related to war. In another example, a lengthy article onlymentions the environment once; the article is given a “weak” rating ofbeing related to the environment. The strength rating is able to be usedin additional calculations in determining importance and/or separatelydisplayed. In the step 1404, the classification of the information iscompared with an importance, where the importance is able to beuser-defined, based on standards or a combination. For example, a useris recognized and has defined his “important” items to be theenvironment, the economy and sports. Furthering the example, if anarticle (e.g. environmental article) matches the user's most importantitem, the article is rated a 10 (e.g. most important). In someembodiments, an importance rating includes a user rating plus thestrength of an article. For example, a user rates the environment as histop priority, and an article is focused on the environment, the articleis rated as most important, but a second article merely mentions theenvironment, the article is rated as moderately important. In the step1406, an importance rating is indicated based on the comparison in thestep 1404. For example, since the user indicated environment as the mostimportant topic to him, and an article is determined to be about theenvironment, the article is given an importance rating of 10, which isdisplayed near the headline as is shown in FIG. 13. In some embodiments,fewer or more steps are implemented. Furthermore, in some embodiments,the order of the steps is modified.

In some embodiments, a channel is automatically changed when atelevision program discusses a story that falls below the user'simportance threshold, for example, by determining the importance of thestory, comparing the importance rating with the threshold, and if theimportance rating is or falls below the threshold, the channel ischanged. In some embodiments, the channel is changed to a story that ismost important to the user. For example, a user has selected 3topics—economy, sports, weather, and the user is watching News ChannelA, when the sports segment ends, and goes to a story about fashion, sothe television automatically switches to Channel B which is discussingthe economy. To make the switch, content on all or specified channels ismonitored and given an importance rating. In some embodiments, a videois changed in a similar manner to changing a channel For example, if awebsite displays videos, and the current video is below an importancethreshold, the next video is presented. Similarly, a radio station orother program is able to be automatically changed based on a user'simportance threshold.

Bias

In some embodiments, a monitor of news stories and/or articlesdetermines if a story and/or article is being ignored or overanalyzed.For example, if 3 of 4 news networks cover a story, and the fourth newsnetwork does not cover the story or barely reports on it, a notificationor alert is presented to inform the user that he is missing the story.This is able to be implemented by comparing the stories, for example,comparing keywords or other information in the stories. This will helpprovide users with a full scope of news knowledge. In some embodiments,the notification includes a link or a guide to change the channel, sothe user is able to see or hear the story. In a similar but contrastingmanner, in some embodiments, stories are monitored to determine if theyare over reported. For example, if the same story is played on allstations, every 10 minutes, a notification or alert is presented toinform the user that the story is being over reported. In someembodiments, users are able to rate stories under reported, overreported or other ratings. For example, users are able to text a rating.Other methods of rating a story are possible as well. News networks arethen able to modify the presentation of news based on users' ratings. Insome embodiments, users register to be able to interact with a show orwebsite. In some embodiments, users have to qualify (e.g. pass a test)to be able to rate and/or post comments. For example, in someembodiments, users must prove they are not “trolls” by accuratelypredicting the factual accuracy of several statements.

In some embodiments, identifying framing of data including, but notlimited to, spin, slant, bias or any other framing or manipulation ofdata is implemented. Identifying framing of data is able to be done inany manner. In some embodiments, a data structure (e.g. a database) isused to store biases including, but not limited to, biased information,biased entities, and other biases. In some embodiments, the bias of thespeaker is able to be used to identify framing. For example, if aspeaker is known to be an ultra-conservative, that knowledge is able tobe used to label framing. In some embodiments, a comparison with otherpeople's take on a subject is used to determine spin. In someembodiments, the comparison is based on peers or groups. For example,news reporters are compared with other news reporters. In an example, if9 commentators label a speech as “well done,” and 1 commentator labelsthe speech as “poor,” the 1 commentator's comments are able to belabeled as “unrepresentative” or “minority view.” Further in theexample, the information that 9 commentators view something one way andthe 1 commentator views it another, is able to be used with additionalinformation (e.g. that the 1 commentator is an ultra-liberal), and the 1commentator's comment is labeled as “liberal spin.” In some embodiments,safeguards are able to be implemented to prevent manipulation such as agroup ganging up against an individual. Additionally, the tone of thecommentator, the number of factual inaccuracies by the commentator, andany other information is able to be taken into account to properly labelthe comments as spin, slant, bias or some other classification/category.In cases of subtle spin, such as where a commentator starts off bydescribing a radical element of a group and then generally applies abroad stroke to the entire group, that is able to be detected as well.For example, antecedent basis is monitored and checked. In an example, acommentator says, “the far right is a bunch of warmongers,” and thenlater, the commentator says, “the right loves to go to war.” While thefirst statement may be true, the second statement is clearly an overlybroad statement and is able to be labeled as “misleading” or is able tobe clarified by adding “far” to the statement to indicate “far right.”Entities including, but not limited to, individuals, commentators,networks, companies and any other entity are able to have labels orother information to help determine a bias or slant. For example,commentators, channels, networks, websites and blogs are able to belabeled with political terms or other terms as described herein.Companies are able to be labeled with political terms as well or otherterms including, but not limited to, anti-environment. Not only do thelabels help identify to a viewer or reader where the information iscoming from, but the labels are able to be quantified to performadditional calculations including, but not limited to, identifying spin.As described herein referring to the slant rating, the labels are ableto be determined using any data including, but not limited to, thenumber of errors, types of errors, statistical analysis, surveys,analysis of content, analysis of past performance, and any otherinformation.

In some embodiments, the fact checker monitors a news story for bias orone-sidedness and presents helpful information to provide a full story.For example, if a news report discusses a police shooting of a suspectbut leaves out the aspect of the story that the suspect fired at thepolice first, the fact checker is able to determine the incompletenessof the story and provide supplemental information in any of the mannersdescribed herein (e.g. a text message of the missing information to theuser's mobile device, an alert that there is more to the story, anemail, or any other method). In an exemplary implementation, a databasewith full details of a story is maintained to compare with the presentedstory, and any information not mentioned in the presented story is ableto be supplemented. In some embodiments, the full detail database iscompiled by searching sources. In another example, if a news programonly discusses negative aspects about an issue, or if a news programonly discusses positive aspects about an issue, such one-sidedness isdetected. In some embodiments, to determine the one-sidedness, theunderlying data of the story is monitored (e.g. the stock market) andthe show/program is monitored, and then they are compared so that if theunderlying data changes but the show/program does not report the change,one-sidedness is detected. Furthering the example, if a show, for 3 daysin a row, mentions the stock market is down, and then the show issubsequently silent when the stock market is up for 4 days in a rowfollowing that, such a characterization is able to be detected. In someembodiments, the information is also presented to users (e.g. scrollingtext saying, “although this program mentioned the stock market beingdown 3 days, the stock market has been up 4 days since then”). In someembodiments, such information is able to be tracked and used to rate thenews program.

In some embodiments, a caller (e.g. of a radio show) or commenter(and/or his comments) is fact checked to determine the quality of thecaller/commenter. For example, the arguments of the caller areclassified as good/poor arguments, the grammar is classified, and otherinformation is taken into account to determine the quality of thecaller. Multiple callers are able to be analyzed to determine if thecallers are being selected to poorly represent one side of an argumentor a group of people. For example, if a radio show selects callers withoutrageous arguments for one side, and reasonable arguments for theother side, such a bias is able to be detected and indicated to users(e.g. listeners).

In some embodiments, supplemental information regarding what percentageof the population agrees or disagrees with a position is displayed. Forexample, a commenter says, “liberals believe in socialism,” and inresponse, an indication of “This view is shared by 20% of people whoconsider themselves ‘liberals’ and 5% of people who consider themselves‘democrats’ is shown.” In some embodiments, specific phrases aremonitored to implement this, such as “liberals believe” or “liberalsthink.”

In some embodiments, bias or other classifications are determined ortracked based solely on analyzing headlines, titles, or other headings.

In some embodiments, polling, ratings or other information are factchecked or analyzed for bias. For example, if a news organization saysthey cover stories with a fair representation of each side since theymentioned each side the same amount of time, further analysis is able tobe performed to determine if each time they had a bias towards one orthe other. And a clarification of bias is able to be presented. In someembodiments, a classification and an indication of sources, polling,organizations and/or other entities is presented. For example, if acommentator cites the XYZ poll, an indication that the XYZ poll is aleft-leaning poll is indicated.

In some embodiments, analysis and/or comparison of the fact checkingdata/results of networks, shows, web sites or other presenters of datais performed. For example, Channel A is found to lie (or err) 20times/day and have 1 stale story/day, and Channel B lies 5 times/day andhas 0 stale stories/day. Other data is able to be tracked including, butnot limited to, historical data and improvements or trends. The resultsand other information are able to be stored, sorted, compared, analyzed,searched, displayed (e.g. chart/graph/numerical), and/or used for manydifferent purposes. The information is also able to be used to generatea results rating. For example, channels are rated based on the number oferrors, number of corrections, timeliness of correction, number of stalestories, and/or any other factors. The results rating is able to be inany form including, but not limited to, 1-5 stars, A-F, 1-10 or 1-3diamonds. A slant rating is able to be used to indicate if a channel,show, site or other item has a political slant including, but notlimited to, liberal, conservative, moderate, or any others. Users arealso able to search, sort or perform other tasks based on the slantrating or other information. For example, users are able to set, sort orsearch channels, web pages, blogs, shows/programs and others, based onthe comparison of a results rating such as searching for all cable newsprograms with a 4 star rating or higher. The searches are able to begeneric or more detailed. For example, a user is able to search for allshows that have 3 stars or better. In an example of a specific search, auser searches for all shows with 4 stars or better, with a moderaterating, in channel range of channels 2-10.

Television/Video/Other Media

In some embodiments, archiving is implemented. For example, televisionshows are recorded or converted to text and recorded. In someembodiments, only fact checked aspects are archived. In someembodiments, only fact checked items that are classified a certain way(e.g. false) are archived. In some embodiments, the archives includegroupings. For example, false statements are in one group, hyperbole isin another group, and other items are in other groups.

In some embodiments, the fact checking is used for analysis ofcommercials. For example, if a law firm advertisement is displayed, thefact checker is able to provide statistics about the law firm including,but not limited to, where the attorneys went to law school, bar ratings,articles about the law firm, the law firm's website link, providecomparison results such as similar law firms and/or any other relevantinformation. In another example, a restaurant displays an advertisementthat is broadcast nationally, and the nearest location is able to bedisplayed by determining the user's location (e.g. the device locationvia GPS and/or IP address). Furthering the example, ratings, menus,nutritional information, allergen information and/or any otherinformation for the restaurant is made available or displayed. Againfurthering the example, a user's mobile device automatically mapsdirections to go to the nearest location from the user's currentlocation. In some embodiments, the fact checker is used to determine thevalidity of commercials. For example, if a commercial claims theadvertised product is the best, the fact checker is able to compare theproduct by searching for ratings on comparison websites, and/or anyother resources to determine if the commercial is true. The fact checkeris also able to present additional information to provide a user moredetail. For example, an automobile commercial claims the displayedvehicle is the #1 rated vehicle. The fact checker verifies the claim andalso informs the viewer that the vehicle is #1 rated for men ages 19-29,but overall, a competitor's vehicle is #1 rated. The fact checker isable to provide automatic comparison shopping. Any commercials oradvertisements are able to be fact checked including, but not limitedto, print, broadcast, digital/online and mobile-based. In someembodiments, a commercial or advertisement is detected based on aproduct, a company and/or language in the commercial/advertisement. Insome embodiments, a commercial/advertisement is detected using anotherimplementation.

In some embodiments, users are able to post comments directly to atelevised show or other video. For example, users send comments to atelevision network or show producer. In some embodiments, the networkfilters the comments. The comments are able to include citations provingor disproving a speaker's comment, or labeling the comment in anothermanner. As described herein, in some embodiments, comments are displayedto a designated group of users. In some embodiments, users are able tobe in more than one group.

In some embodiments, group video viewing is implemented. For example, aspecific group of users watch a video at the same time and are able topost comments and perform other fact checking aspects on the video.Users are able to invite others to join the group. In a further example,a set of co-workers form a viewing group to watch the State of the UnionAddress. While the State of the Union Address is displayed, the usersare able to input (e.g. tweet, instant message, text) comments about thespeech which are shown to the other users in the group. If the automaticfact checker is implemented, then the speech is automatically factchecked as well. If the automatic fact checker is not implemented, usersare able to flag items to be fact checked. Additionally, users are ableto flag other users' comments, or users' comments are automatically factchecked, depending on the implementation. The groups are able to be assmall as two people (e.g. husband and wife viewing the same video fromdifferent locations) or as large as an entire population (e.g.billions). The groups are configurable in many ways. Users can be addedto groups, deleted from groups, be in multiple groups, and any othergrouping features are able to be implemented.

In some embodiments, television analysis is performed. For example, thefact checker monitors video and audio, converts the audio to text andanalyzes the text to provide information of what is going on in thevideo in real-time. The fact checking process is able to occur in thebackground, so that the user is able to view other channels. Bymonitoring and analyzing the video in the background, the fact checkeris able to then inform a user when it detects information the user islooking for. For example, there is a sports show on Channel 50 whichdiscusses all different sporting events such as baseball, golf, soccerand basketball, but the user simply wants a recap of golf scores. Theuser is able to input a search string (e.g. golf), or the systemautomatically knows what to look for based on previous searches or otherinformation (e.g. trending information), or another implementation isused to monitor. The fact checker analyzes the text of the show for theword “golf” or a related word/name/item such as par, U.S. Open, Tiger,and when the word is found, the user is alerted that his topic is beingdisplayed on that channel, so that the user knows to change to thatchannel This enables users to avoid having to constantly switch back andforth to find a desired segment. In some embodiments, the informationmonitored is an actor, a location, and/or any other information. In someembodiments, images are monitored (e.g. a user selects an image of anactor, and that image is compared with the broadcast information todetermine a match). In some embodiments, when the correct segment isbeing displayed, the channel automatically changes for the user. In someembodiments, a picture-in-picture window of the other channel isdisplayed. In some embodiments, an audible or other alert is presentedto inform the user. In some embodiments, the fact checker is able to beused to alert a user that a commercial is over, and that the desiredshow has returned. In some embodiments, the fact checker is used inconjunction with a recording device, for example, a Digital VideoRecorder (DVR) (e.g. TiVo®). After audio is converted to text, a searchis able to be performed on the text. For example, an entire sports showis recorded and converted. A search for “Tiger Woods” is performed bythe user. The text is searched, and when the phrase “Tiger Woods” isfound, the video begins playing from that point in the video (e.g. inthe video, a commentator mentions the name “Tiger Woods”). In someembodiments, every instance of the search phrase is found, so that theuser is able to jump to each instance of the search phrase in the video.For example, if “Tiger Woods” is discussed at 5:59, 10:32 and 50:21 ofthe video, the user is able to hit a “Next” or “Previous” button tonavigate to each point in the video where “Tiger Woods” is mentioned.Any search techniques and/or features are able to be implemented. Insome embodiments, instead of a conversion of audio to text, text isprovided in advance or during the show. For example, networks are ableto provide text from the show in a searchable form. In some embodiments,converted text or other text is also able to be used to predict futuretelevision information. For example, a news program states that storiesabout A, B and C will be shown tonight. The fact checker is able todetermine when the specific stories of A, B and C will actually air, sothat users are able to avoid stories they are not interested in. Thetelevision analysis is also able to be applied to other forms of mediaincluding, but not limited to, radio, Internet webcasts, videos and anyother media. For example, the fact checker is able to monitor some orall radio stations for a desired song and when that song is found, thestation switches to play that song. The search is able to be used tofind a song by a title, artist, based on several words of the song (e.g.first three words), or some other method.

In some embodiments, re-runs or replays of shows do not use additionalfact checking For example, if a show is typically displayed at 5 pm andthen replayed at 8 pm, the 8 pm show is able to use the previous factcheck information from the 5 pm show. In some embodiments, additionalinformation is provided in the 5 pm show that was not provided in the 5pm show. In some embodiments, analysis is performed to confirm the showsare the same.

In some embodiments, the fact checking is performed using an originalbroadcast and then displayed during a repeat broadcast or a recordedbroadcast. In this implementation, the fact checking is able to be inreal-time or non-real-time, automatically or not automatically. Forexample, a show is broadcast at 5 pm, and fact checking occurs. Then,when the show is re-broadcast at 8 pm, fact checking results/informationis presented automatically and in real-time during the re-broadcast.Similarly, when a re-broadcast occurs via the Internet, such as on abroadcaster's website, results/information is presented during there-broadcast. Although this would not prevent misinformation from beingspread in the initial broadcast, the fact that any re-broadcasts wouldcatch any misinformation could potentially discourage misinformationfrom being presented in the initial broadcast. In an exemplary manualimplementation, viewers watching the 5 pm telecast flag information asmisleading, incorrect, unclear and/or any other characterization, thenfact checking and/or other analysis is performed, and then at a latertelecast (e.g. the 8 pm telecast), corrective and/or supplementalinformation is displayed automatically to the viewers of the latertelecast at the appropriate times. The appropriate times are able to bedetermined in any manner, including, but not limited to, monitoring forkeywords (e.g. database includes keywords to monitor and correspondingcorrective comments to display), monitoring for a designated time (e.g.each time a user flags information, a timestamp is made which is thenused to display the corrective comments) and/or any other method.

In some embodiments, polling occurs during a broadcast and then isposted during the re-airing of the show. For example, a poll ispresented, “conservatives, do you agree with Commentator A's position,”and people respond, and then the results are shown that “earlier pollsshow X % polled agree with this position.”

In some embodiments, the fact checking system is used to avoid orcorrect a mistake presented. For example, in the past, news networkshave accidentally posted graphics with incorrect statistics. The factchecking system is able to preemptively check the graphics orpost-display check the graphics, so that the poster (e.g. network) isable to correct the error before broadcasting the error or quicklythereafter.

In some embodiments, automatic prediction tracking is implemented. Forexample, a commentator says, “President Z is going to lose in 2012.”That comment is stored, and once a result is determined (e.g. theelection ends), the accuracy of the prediction is determined (e.g. usingthe fact checker). In some embodiments, the prediction determinationsare stored, used for statistics, to generate prediction ratings/accuracyratings and/or for any other purposes. For example, commentators or anyother entities that make predictions are able to have prediction ratingsso that viewers are able to see how accurate commentator's predictionsare. For example, when a commentator is shown on television, aprediction rating is shown (e.g. correct predictions 5, incorrectpredictions 10) to indicate to viewers that this commentator'spredictions do not usually come true. The prediction ratings are able tobe in any form such as grades (A-F) or any other rating scheme. In someembodiments, multiple categories of predictions ratings per entity areimplemented. For example, a sports analyst may predict football well butnot baseball, so his rating for football is high but for baseball islow. Examples of entities that make predictions, guesses or estimatesinclude but are not limited to, commentators, weathermen, stockcommentators, news commentators, businesses, sports commentators, realestate commentators, analysts, financial commentators, entertainmentcommentators, reality show hosts/judges, and/or any other entity.

In some embodiments, the fact checking system is used to rate weatherpredictors. For example, if one channel is wrong more often thananother, viewers would be informed of this and could change theirviewing habits accordingly. In some embodiments, viewers are given alist of alternatives. For example, a list of channels with accuracypercentages is displayed.

In some embodiments, a stock picker is fact checked to determine theaccuracy of stock pickers. For example, if an online site boasts aboutbeing able to select stocks, the fact checker is able to monitor thepicked stocks and then provide an accuracy rating for the site, so thatusers are able to use the most accurate site. Similarly, sports analystsare fact checked and tracked to indicate the accuracy of the sportsanalysts' predictions/picks.

In some embodiments, the fact checker indicates a status of a comment tothe host/interviewer of a show (e.g. so that the host is able to ask afollow-up question). In some embodiments, the fact checker comes up withthe follow-up question automatically (e.g. follow up question isdisplayed on teleprompter). For example, if a host asks a guest what theguest does not like about the President, and the guest responds that“taxes are too high.” The fact checker is able to determine that thecurrent President has lowered taxes since becoming President, andautomatically generate a follow-up question of, “since the President haslowered taxes, is that a valid complaint about the President?” In someembodiments, the follow-up question is based on searches performed bythe fact checker. In some embodiments, a database of potential follow-upquestions is implemented and based on the answer, a follow-up questionis selected.

In some embodiments, an avatar or other representation of an entity isdisplayed on a show (e.g. a television show or webcast) to present thefact checking information. For example, a political commentary show hasguests, and one of the guests is able to be an avatar that comments whenone of the other guests or the host makes a misstatement or some otherstatement that warrants commenting. The avatar is able to becomputer-generated or any other type of generated avatar.

In some embodiments, the severity (e.g. severity of incorrectness,severity of bias, severity of political slant) of a statement isindicated with the result. For example, if a person says, “Rhode Islandis the largest state,” a severity rating of 10 is displayed as thestatement is completely wrong since Rhode Island is the smallest state.In another example, if a person shows extreme bias, a bias severityrating of 10 is displayed. The severity rating is able to be indicatedin any manner, including, but not limited to, 1-10, by grades including,but not limited to A-F, bright colors indicating severe and dull colorsindicating not severe, imagery/pictures, audio (e.g. “wow!” for severe,“wah wah” for not severe, or a loud chime for severe, a quiet chime forless severe), or any other rating, grading or indicating system.

In some embodiments, the fact checker is used to inform a person (e.g. ahost) that he made a mistake. For example, a host states the U.S. is $15Billion in debt, and a chime and/or other audio is emitted in the host'searpiece, letting the host know that he made a mistake. In someembodiments, the chime is merely just a short chime where the host hasto figure out what the mistake was, and in some embodiments, the audiois a correction (e.g. “Trillion” in this example) or a chime linked to ateleprompter that could display accurate information or incorrectstatement. In some embodiments, the indicator to the person is visual(e.g. a flashing red light), tactile (e.g. vibration), or any otherindicator.

In some embodiments, a host, guest or other entity is providedadditional information (e.g. statistics) by the fact checker during acommunication. In some embodiments, additional information is indicatedwhen questionable information or other information is presented. Forexample, in a debate, debater A is able to have the fact checker runningwhile debater B is making comments. Debater A is then able to use thefact checked information to debate better.

In some embodiments, using the fact checker, if a commentator (e.g.guest) is found to have misstated facts a specified number of times(e.g. 3 times) within a specified period of time, an action isautomatically taken against the guest (e.g. the guest's microphone iscut off for a period of time). For example, a guest is on a politicalcommentary show, and he makes 3 factually inaccurate statements on theshow, his microphone is cut off (silenced) for 1 minute. In addition tofact checking, other events are able to contribute towards taking theaction. For example, if a guest keeps interrupting other guests, eachinterruption could contribute toward taking action. For example, a guestinterrupts once and makes two factually inaccurate statements; those 3events cause the action to be taken against the guest. Another exampleof an action is shining a colored light (e.g. a red light) on the entityfor a period of time. In another example, when a score is maintained todetermine the winner of the argument on the show, an action includesdisqualifying a participant or deducting points due to improper conduct.The action is able to be taken against any entity, not only a guest, andany actions are able to be taken.

In some embodiments, points are awarded to hosts, guests,callers/commenters and/or others based on their arguments to determinewho wins an argument. The points are able to be awarded based one ormore factors including, but not limited to, factual accuracy/inaccuracyof the arguments, conduct, viewer voting, judge voting, and/or any otherfactors. The point tally is able to be kept running while the argumentoccurs and/or indicated at the end of the argument. For example, apolitical commentary show includes a segment with a host debating aguest on a controversial topic. The host and the guest each go back andforth presenting their arguments. The fact checker automaticallymonitors, processes, and fact checks the arguments and then gives pointsfor factually accurate information, and deducts points for inaccurateinformation. The fact checker also determines if improper conductoccurs, for example, cutting off the other or filibustering (e.g. notanswering the question directly), and deducts accordingly. While thesegment is airing, or quickly thereafter, users are able to vote (e.g.by text or any other implementation) for who is winning/won theargument. A formula is able to be implemented to add the votes with thefact checker results to determine a score (e.g. whoever wins eachargument receives a point which is added to the fact checker points).Then at the end of the segment or some other point in the show, theresults are displayed, indicating a winner of the argument (e.g. the onewith the most points). In some embodiments, a host is given a handicap(e.g. host starts with a 1 point reduction) in an attempt to balance thelikely bias of his viewers. In some embodiments, users are able toselect the factors used in determining a winner. For example, if a userdoes not like the idea of other users affecting the outcome, the user isable to specify that the winner is determined solely based on the factchecker results.

In some embodiments, when an entity communicates (e.g. speaks or writes)or is displayed, donors and/or contributors who have contributed to himor his campaign and/or charities or other entities he has contributed toare displayed. For example, a politician is shown on television, and alist of the top 10 contributors to his campaign is displayed on a user'smobile device. In some embodiments, only contributors related to a topic(e.g. discussing energy, display oil company contributions). Any amountof information about the contributors is able to be displayed (e.g. howmuch in contributions, when the contributions were made, and otherinformation). The contribution information is able to be determinedusing a data structure (e.g. a database) which stores entities andrelated contribution information, via searching as described herein orany other method.

In some embodiments, a list of names of supporters and/or dissenters ofinformation is presented. The list is stored in a data structure such asa database and/or is based on previous comments, writings and/or otherinformation. For example, a guest on a talk show makes the comment:“lower taxes creates jobs,” and a list of prominent people supportingthat position is displayed.

In some embodiments, the fact checker is used to assist users in readingthe fine print displayed in television advertisements. For example, thefact checker captures the fine print and allows the reader to displaythe fine print for longer than the normal display time. In anotherexample, the fact checker allows the user to capture and enlarge thefine print so that it is more legible.

In some embodiments, to determine a character/actor/location/otherinformation, a user takes a picture of a television screen, computerscreen, mobile device screen or any other object/scene. For example, ifa movie is being played on a person's television, the person uses hismobile device to take a picture of the screen, and then the mobiledevice is able to analyze the picture and determine the actor, moviebeing played, where the set location is, and/or provide any otherinformation.

In some embodiments, when a poll is referred to, related polls aresearched for and presented. In some embodiments, the polls are compared.For example, Political Program X only shows an XYZ poll that showsCandidate Z in the lead, but a similar poll (ZZZ poll) shows Candidate Yin the lead, then the ZZZ poll is also presented. Similar polls are ableto be searched for in any manner, including, but not limited to, same orsimilar dates, same or similar topics and/or any other manner.

In some embodiments, a mobile device (e.g. smart phone) is used to scana television advertisement to obtain information. For example, if a useris watching television and a commercial appears, the user holds hismobile device with camera so that the camera is able to scan thecommercial, and then the user is able to click on an item in theadvertisement or entire advertisement to receive additional informationregarding the item and/or advertisement. In some embodiments, the useris able to transfer the advertisement to his mobile device (e.g. bypointing the camera of the mobile device at the advertisement andselecting “transfer” or “capture”).

In some embodiments, fact check information and/or supplementalinformation is indicated while a user is fast-forwarding, pausing and/ortaking another action with a video. For example, while a user isfast-forwarding a DVD, supplemental information is displayed to theuser.

In some embodiments, a DVR records a show with or without fact checkedinformation or supplemental information, but fact checked informationand/or supplemental information is determined in the time between theinitial recording of the show by the DVR and when the user views therecorded information, so that when a user views the recordedinformation, the fact checked results and/or supplemental information isdisplayed. In some embodiments, the fact checked results and/orsupplemental information is stored on the DVR, and in some embodiments,the information is stored on another device. In some embodiments, thefact checked results and/or supplemental information is updatedincrementally as new information is determined.

In some embodiments, supplemental information that includes a fusion ofgenres is implemented. For example, a user is watching a politicalcommentary show and comedic supplemental information is provided. Thedetermination of the supplemental information to provide is the same asor similar to other implementations described herein. In someembodiments, a database of keywords and corresponding actions to take orinformation to display is maintained, or the actions or information arebased on searches performed. For example, a database includes a keyword“global warming” and a joke related to global warming is included tocorrespond with that keyword. Then, as the information is monitored, andthe keyword is detected, the joke is presented to the user (e.g. on hismobile device or television). In some embodiments, more information isused in determining what supplemental information is displayed. Forexample, user-related information is used including, but not limited to,age, gender, location, political leaning, and any other information.Furthering the example, if a user is conservative, a joke linked toglobal warming would be critical of global warming; whereas, a joke fora liberal user would be critical of those who do not believe in globalwarming. In some embodiments, a personalized viewing schedule isimplemented. The personalized viewing schedule is able to be implementedby switching among channels, using a video recording system (e.g. DVR orTiVo®), using online video, using radio and/or any other implementation.For example, after the fact checker monitors and processes a 10 pm newsprogram, in conjunction with a DVR storing the news program, the factchecker displays a list of topics/stories covered in the news program.Furthering the example, the 10 pm news includes a stock market report, ahomicide report, a weather report, a sports report, and a story aboutlocal art projects. The user is presented these items (e.g. in a list),and then the user is able to select and/or rank the stories to watch inorder or select only particular stories to view. For example, the userchooses to watch the sports report, the stock market report and theweather report, and then only those stories are shown to the user. Insome embodiments, the items (or segments) are pre-sorted based onprevious selections by the user, user preferences, friends' selections(e.g. Facebook contact recommendations), popularity, and/or any otherbases. In some embodiments, the list of stories is displayed on thescreen, so that the user is able to see what stories are upcoming.

In some embodiments, the fact check information and/or supplementalinformation is displayed as part of and/or during a commercial break.

In some embodiments, a fact checker button is implemented for turningon/off the fact checking system. The fact checker button is able to belocated on a remote control, television, mobile device and/or any otherdevice and is able to be a hard button, soft key, menu selection, or anyother implementation.

In some embodiments, the fact checker is implemented such that themonitoring, processing, and fact checking are performed automatically,but a user (e.g. moderator) is also involved with the indicating suchthat it is performed semi-automatically. For example, a person's speechis monitored, processed and fact checked automatically, and then theresults of the fact check are displayed to a moderator who is able todetermine which fact check results are indicated (e.g. displayed toviewers). For further example, the fact checker finds that the speakermisspoke and said $100 Billion instead of $100 Million. The fact checkerpresents this to the moderator who then approves the correction which isthen posted to viewer's screens. Although this slows down the processslightly, the delay will be minimal such that the indication is stillpresented within several seconds and possibly even within one second.

Additional Structure and Execution

In some embodiments, a device such as a mobile device is used to performa fact check of an item through the use of the device's camera or othersensor. The mobile device is able to scan (e.g. merely point camerawithout taking picture), take a picture, take a video, or any othermethod of acquiring the content of the item. For example, a mobile phoneis used to take a picture of a print newspaper and perform a fact checkof the newspaper. The writers of the articles are able to be rated asdescribed herein. The newspaper or magazine is able to be rated asdescribed herein. For example, tabloids are viewed as unreliable or aregiven less credibility than a standard newspaper. Any print material isable to be fact checked, including, but not limited to, newspapers,magazines, books, billboards and pamphlets, including any advertisementswithin. In some embodiments, the device is able to fact check an itemincluding, but not limited to, a purse, dress, watch, ring, shoe, suit,clothing, or any other item to determine the brand of the item and/or ifthe item is a replica. For example, a user directs the camera of hismobile phone toward a watch and the fact checker determines if the watchis an original Rolex or a replica. The fact checker is able to performthe check in any manner such as determining that the watch says Molexinstead of Rolex, or by a picture comparison of the acquired watch andcertified watches stored in a database, comparing distinct features of agenuine article such as stitching and/or hardware/material used, or anyother comparison.

In some embodiments, the item determination is performed on items ontelevision, the Internet or elsewhere. For example, during an awardsshow, the item determination posts information about the dresses beingworn, including, but not limited to, designer and/or price. The factchecker is also able to perform person identification. Using the awardsshow example, an indication of who is being shown on camera is able tobe displayed. As described herein, facial/body analysis or any othermethod is able to be performed to determine who people are.Additionally, character/actor/person determination is able to beperformed. For example, if a commercial is being displayed, and a useris curious who the main actor is, actor determination is implemented todisplay the actor's information. In some embodiments, allcharacter/actor information is displayed, only selected character/actorinformation is displayed, or any other configuration of information isdisplayed. For example, all names of actors on a television show areshown under each actor. In another example, a user specifically selects(e.g. by touchscreen or any other method of selecting) the actor to seeinformation. The amount of information is also able to be variable. Forexample, as little as a name is shown or much more detailed informationis shown including, but not limited to, biographical information, othershows/movies, ratings/reviews, links, character/plot summary (e.g. asummary of this character's involvement in the plot) and any otherinformation. In some embodiments, information about when a specifiedactor will be on television next is displayed. For example, a userclicks on Actor A, and the user is informed that the actor is also inMovie Z, at 7 pm on Channel 263. For sports, some or all names of theplayers are shown on/near each player. In another example, a userspecifically selects (e.g. by touchscreen or any other method ofselecting) the player to see information. The amount of information isalso able to be variable (e.g. game stats, historical stats, personalinformation, fantasy football stats, and any other information). Thefact checker is also able to perform location recognition. For example,if a reporter is “on location,” the fact checker is able to determinewhere that location is. The fact checker is able to determine thelocation by comparing the image with a stored image, by searching thecredits (e.g. a movie specifies locations of shootings), by searchingtext of the transcript (e.g. newscaster earlier said, “we're on locationlive at x,” and/or any other implementation. In some embodiments, aftera location is determined, the viewer is able to pull up additionalinformation about the location (e.g. historical information, currentinformation (weather, prices of goods)). Character determination,location determination and any other determination is able to beimplemented using any media including, but not limited to, television,movies, photographs (e.g. online photographs), videos (e.g. onlinevideos), satellite information, prior news feeds, or any other media. Insome embodiments, identifying the object is by comparing the object withother objects in the scene, finding a story/article about the object, orany other method of identification. Distances and/or sizes of objectswithin the scene are able to be determined with scene analysis.

In some embodiments, the fact checker checks for and indicatesdefamation, slander, libel, plagiarism, copyright infringement,trademark infringement, patent infringement, and/or other crimes. Insome embodiments, when a crime is committed or may have been committed,the targeted person and/or someone else (e.g. the police) is contacted(e.g. an email or Tweet is sent with the criminal comment, whosaid/wrote the comment, and any other relevant information). In someembodiments, defamation or other crimes are determined by: determiningthe location of the speaker or victim, determining if the statement isfalse, determining state law and presenting the state law and statementto the victim or the victim's attorney and/or analyzing the law todetermine if the law is violated. In some embodiments, additionalelements are considered such as defenses to the crime. In someembodiments, other crimes/laws are fact checked by analyzing thelaw/statute/regulation/ordinance/cases/other information, analyzing thefacts and determining a result. In some embodiments, a database of laws,cases and holdings is used to perform the analysis. In some embodiments,the analysis merely returns similar cases, so that the user is able tocompare. In a same or similar manner, a disparaging comment is detectedand reported (e.g. to the target of the comment). For example, ifsomeone writes on a message board that Company XYZ is a terriblecompany, the comment, web address, citation, and/or any otherinformation is sent (e.g. by email, Twitter or any other means) to thetarget of the comment. In some embodiments, future shows and/or newsstories are based on fact checking results. For example, if usersrespond to news stories as overplayed, future newscasts will not includestories related to that topic. In another example, if users request moreinformation about an aspect of the story (e.g. victim's race), futurenewscasts will include that information. In another example, if usersrate a story as “biased,” the future newscast will remove the bias.

In some embodiments, an indication on or near a headline, title,caption, talking point and/or other short phrase is implemented. Forexample, a rating of a story, article, news or any other information isable to be implemented. In some embodiments, the rating of the story isbased on an automatic fact check of the story. In a further example, atitle of an article is “Vaccines Proven Harmful,” but the article usesstudies that have been discredited and readers rate the article poorly,future viewers will see the article as “Vaccines Proven Harmful 0Stars.” In some embodiments, the indication is not near the headline orother phrase. For example, the indication is on a user's mobile deviceafter scanning or taking a picture of a hardcopy title. In someembodiments, the indication is a characterization of the article. Forexample, the article is characterized as liberal, neutral orconservative. Other characterizations, ratings and indications are ableto be implemented. In some embodiments, an indication of a better and/oropposing article, story and/or other information is indicated. In someembodiments, if a headline is determined to be misleading (e.g. bycomparing the headline with the content of the article and/or based onuser reviews), an indication of “misleading” is displayed near theheadline.

In some embodiments, stories (e.g. articles, news stories, and other)are rated. For example, if users are tired of hearing about Story X,users are able to communicate that opinion. In some embodiments,broadcasters and/or reporters are able to receive the ratingsinformation automatically, so that they are able to cut short, extend orotherwise modify the programming. In some embodiments, users are able toprovide more specifics about the rating of the story. For example, aviewer is able to indicate she is tired of the slanted presentation ofthe story or the presentation of the lineup of stories (e.g. alwaysmaking criminals looking like they were unfairly treated by leaving outimportant details). The ratings are able to be any form of ratingsincluding, but not limited to, thumbs up/down, good/bad, 1-10, A-F,emoticons, a selection from a list of choices, and/or any otherimplementation.

In some embodiments, a self-checking system is implemented. For example,a mobile device application including, but not limited to, an iPhone®App, monitors a person's comments when he speaks, and if the person sayssomething incorrect, the application alerts (e.g. chime, ringtone) theperson. For further example, a dad is explaining geography to hisdaughter and says Alabama is West of Mississippi; the applicationchimes. In some embodiments, the application provides a correction,provides a citation and/or any other information to help the person. Insome embodiments, the self-checking is able to be implemented to providepositive feedback for saying a correct statement, for example, as alearning tool or a game for children. In some embodiments, a quiz, amultiple choice program, or other testing material is implemented. Insome embodiments, the fact checker fact checks a user's statement andthen asks a question related to the statement. In some embodiments, thefact checker learns based on the result of the fact check to ask anadditional question. In some embodiments, based on a series ofstatements by the user, the fact checker asks the user a question. Insome embodiments, the self-checking system has the ability to only factcheck a specified user (e.g. by voice recognition or some otherrecognition) so that other people's comments are not fact checked. Forexample, if a user implements a self-checking iPhone® application whichmonitors everything received by the iPhone® listening device, then whilethe user is walking on the street, conversations of others may be factchecked. If the user does not want these other conversations factchecked, the specified user implementation is able to filter receivedinformation, and only fact check statements made by the specified user.

In some embodiments, the fact checking is implemented in or as a searchengine and/or a browser. Using a standard search engine, entering astatement such as “Alaska is the largest state” results in links beingdisplayed on the screen which enable a user to then select a link wherethe user is able to verify if Alaska is the largest state. Using a factchecking enabled search engine, a user is able to enter “Alaska is thelargest state” in the browser window, and the result of “True” appears.In some embodiments, links still appear as from a standard searchengine, and next to or near each link appears a result including, butnot limited to, True/False or any other indicators. In some embodiments,search engine capabilities are available in other software (e.g. wordprocessors) to perform a fact check.

In some embodiments, the fact checking system is embedded or used with aword processor including, but not limited to, Microsoft® Word or anyother software program. In some embodiments, the word processorhighlights, underlines, circles, auto-corrects or performs another formof fact checking identification. In some embodiments, if the statementbeing fact checked could be corrected in more than one way, a user ispresented with multiple options. For example, if a user types, “Texas isthe biggest state,” the user is able to be presented with “Alaska” as areplacement of Texas, or “second biggest state,” to clarify that Texasis the second biggest state.

In some embodiments, the fact checker is implemented as part of anoperating system.

In some embodiments, some or every tweet a person sends out ishighlighted or color-coded based on the type of tweet. For example,different tweets are coded as factually correct, factually incorrect,spin, opinion, hyperbole, or any other characterization.

In some embodiments, email is fact checked. Depending on the embodiment,the email is fact checked before being sent out or fact checked when theemail arrives in a user's inbox, or when the user opens the email. Insome embodiments, when the user opens the email, the email is able to beprovided marked up such that factually inaccurate statements areindicated, for example. In some embodiments, a user is able to send theemail to a service, and the service returns a marked up version. Theservice is able to be local to the device (e.g. software running on auser's device) or could be external including, but not limited to, onthe Web. The same or similar implementations are able to be used for SMStexts, MMS texts, audio texts, or any other communication. In someembodiments, an entire email or other message is indicated as “spam” orany other indication/label if it is found to be factually inaccurate. Insome embodiments, a threshold is implemented to determine if the messageis spam. For example, if the threshold is 10 inaccuracies, and 11factually inaccurate items are found, then the message is labeled asspam.

In some embodiments, conversations are recorded for a time period (e.g.a night) so that they are able to be used later for comparison with astatement.

In some embodiments, a closed system of information is searchable, suchas for a court case. For example, all documents, testimony and evidenceare put in a searchable digital format, and if someone makes aconflicting statement compared to what is on the record, an alert or asimilar effect is presented. In some embodiments, all of the searchableinformation is fact checked. In some embodiments, the fact checkerperforms a document reviewer's task. In some embodiments, legalarguments are fact checked to make sure a case is not cited out ofcontext, a holding is not misstated, and/or any other checking.

In some embodiments, a language translator is implemented. For example,a video is translated from one language to another using closed caption.In another example, only mistakes are translated and displayed. In someembodiments, a foreign language monitor is implemented. For example, ifa device knows a user's native language is English, and the user isattempting to speak Spanish, the device monitors for incorrect usage orpronunciation. In some embodiments, the device monitors every languagefor incorrect usage or pronunciation. For example, if a user says, “youplayed good today,” the device is able to correct the user and indicatethe sentence should have been, “you played well today.” In someembodiments, the fact checker checks for outdated word use.

In some embodiments, if a comment is made about an individual, a group,a company or any other entity, that person is able to post a commentrebutting the comment on a different location than the original comment.Or the rebuttal is on the person's website and pulled, or tweeted,spoken, or any other means. For example, if Person A says Person B plansto raise taxes, the fact checking system is able to pull a quote fromPerson B's website that says, “I promise not to raise taxes,” and thatcomment is automatically posted with Person A's comment, providing areal-time rebuttal. The rebuttal is able to be made/posted before theopposing comment is made for an immediate rebuttal. The location of therebuttal is able to be found in any manner such as by determining thename of the person being commented on and finding the person's personalwebsite (e.g. Facebook® page).

In some embodiments, the fact checker is used to prevent bullying onsocial networking sites including, but not limited to, Facebook®,Myspace, LinkedIn, Twitter, and other websites. For example, users areable to flag other poster's comments or pages as false or any othercharacterization. Additionally, as described above, an automaticrebuttal is able to be implemented such that if a user posts somethingon his site and then other users post a contradictory remark on theirsites, the user's post is automatically used to rebut the other users'comments. For example, if a group of users try to disseminate a rumorabout Teen X, Teen X is able to post a remark on his page that the rumoris not true. Then, when the group of users post their rumor on theirsites, their comments will be marked on their sites, and they will berebutted immediately, helping to dispel the rumor. The user is able topost his rebuttal proactively or after the other remarks are alreadymade.

In some embodiments, real estate prices/values are fact checked. Forexample, if a real estate agent tells a person, “this house is worth$500,000,” the fact checking system is able to take data regarding thehouse and do a real-time comparison with comparable sales (and otherfactors or specific information related to the house or the purchaseincluding, but not limited to, household incomes, unemployment rates,population growth, upgrades, and others) and determine the validity ofthe agent's price. Other price comparison is able to be performed aswell such as with tradespeople. For example, if a plumber quotes aperson $100 to replace a pipe, the fact checking system is able todetermine what other plumbers in the area charge for such a task and/orcompare BBB ratings. In some embodiments, a rent checker is implemented.In some embodiments, other price comparison is performed including, butnot limited to, comparison of stores, online goods/services or any othergoods/services.

In an example of live fact checking, while a sporting event is beingbroadcast, a commentator provides commentary including statistics whichare usually fed to the commentator by someone behind the scenes. Tofurther ensure the accuracy of the comments, the fact checker is able tobe implemented to monitor the data fed to the commentator before thecommentator presents it or after the commentator makes the statement, sothat he is able to make any corrections.

In some embodiments, a picture-in-picture configuration is used toprovide information and results from the fact checking system to a user.In some embodiments, picture-in-picture is not used.

In some embodiments, the fact checking system is used to fact checkarchived data. For example, a network's past footage is fact checked.The results of the archived data are able to be used in rating thenetwork or for other purposes.

In some embodiments, hypocrisy is detected. For example, statements arecompared to source information to determine if previous statementscontradict or are hypocritical. For example, Speaker A says, “we shoulddo X” and then two weeks later, Speaker A says, “we should not do X,”the second statement is indicated as hypocritical or flip-flopping. Insome embodiments, the first statement is then displayed. Context is ableto be implemented in conjunction with searching for hypocriticalstatements. For example, if Speaker A says, “adultery is wrong,” butsources show that Speaker A previously committed adultery, an indicationthat Speaker A is being hypocritical is presented. Any other methods ofdetermining hypocrisy are able to be implemented. Further, hypocrisy isable to be included with the validity rating of entities describedherein. For example, when Speaker A appears on a television program, alabel of hypocrite and/or a number of hypocritical statements/actions ispresented. In some embodiments, dates or time frames are used indetermining the relevance of fact check comparison. For example, if ahypocritical statement was made 30 years ago, the fact checker mayrealize that it was more likely a change of view rather than ahypocritical statement; whereas, a contradictory statement made 2 weeksago is likely due to hypocrisy not a change of view. In someembodiments, items similar to hypocrisy including, but not limited to,flip-flopping and waffling are detected. In some embodiments, dates ofwhen the conflicting (e.g. hypocritical) statements/actions occurred aredisplayed. Contradictions and other similar items are able to bedetermined in any manner, including, but not limited to, logiccomparisons. For example, sentences with and without “not” are compared.In another example, detecting antonyms is used. In another example, adata structure (e.g. database) of quotes is kept and the quotes areclassified (e.g. pro-tax), and if quotes by the same entity are onopposite classifications, hypocrisy is determined. Furthering theexample, a commentator says we should attack Country A, which isclassified as pro-war with Country A, and then later the commentatorsays we should not attack Country A, which is classified in an opposingcell as anti-war with Country A, hypocrisy is detected and indicated. Insome embodiments, a database of potentially hypocriticalstatements/actions is maintained and monitored for contradictions. Forexample, the database includes names/entities and correspondingstatements that are most ripe for hypocrisy (e.g. positions on adultery,wasting money, other political positions).

In some embodiments, subscriptions are implemented. Subscriptions areable to be implemented to perform any variety of subscription services.For example, users are able to subscribe to or unsubscribe to factchecking being displayed on their television screen. In someembodiments, users are able to subscribe to different levels of factchecking. In some embodiments, users are able to select preferencesand/or settings for the extent of or quantity of items to be factchecked.

In some embodiments, the fact checker is used with rating websitesincluding, but not limited to, yelp.com to ensure the comments/reviewsby users are accurate. For example, if a user states that Business X isthe worst in State Z, but Business X is not even in State Z, the commentis able to be filtered.

In some embodiments, the fact checker is used for fact checking sports'rules and the implementation of the rules. For example, the fact checkeris used for determining if the umpire/referee made the correct call. Thefact checker is able to analyze video or images of the sport, determinethe applicable rule, analyze the facts and the rule, and produce ajudgment. In some embodiments, the fact checker is used to fact checkpersonal information. For example, a potential employer uses the factchecker to fact check potential employees' resumés. The fact checker isable to take portions of the person's resumé and compare the person'seducation with education records, previous job history with companyinformation, Bar information with public legal databases, and any otherinformation. In another example, a mortgage company uses the factchecker to fact check a potential borrower's mortgage application. Inyet another example, a dating service uses the fact checker to factcheck people's postings. In another example, health information ischecked, and to verify that a person qualifies for life insurance, theperson's application is fact checked based on medical records. The factchecker is able to be used based solely on what is in a person'sdocument (e.g. resumé) or based on other information as well. Forexample, in some embodiments, a person's name is able to be used tolocate supplemental information regarding the person. For example, theperson's web page, Facebook® page, previous papers/articles written andany other information is able to be found to supplement the informationprovided. In some embodiments, only public information is searched, insome embodiments, only private information is searched, and in someembodiments, both public and private information is searched.

In some embodiments, the fact checker is able to be used to providedetails regarding a physical object. For example, if a user takes apicture of a painted wall, the fact checker is able to determine thecolor, brand, type and/or any other information about the paint bydatabase, based on date, location and any other information. In anotherexample, the physical object determination is able to be used forlearning, such that a person is able to take a picture of an object andthe fact checker provides information about the object. For example, achild takes a picture of a cat, and the fact checker tells the childthat it is a cat and that the cat is gray. In some embodiments,additional information is provided including, but not limited to,history of cats, anatomy of cats, and any other information. In someembodiments, the user takes a picture and then inputs (e.g. voice input)what the user thinks the object is, then the fact checker determines ifthe user is correct. For example, a child takes a picture of a cat andsays, “dog,” the fact checker will determine that the object is a catand inform the user of that he is wrong and/or provide the correctanswer. In some embodiments, a game is played using the fact checkerwhere after the user takes the picture, the fact checker asks a questionabout the object. For example, a child takes a picture of the cat, and aquestion of what color the cat is, is presented. The fact checker thenanalyzes the response and responds accordingly. More difficult questionsare able to be asked as well, such as historical questions (e.g. whichgroup worshipped cats?), geography questions (e.g. what country has themost cats?), and/or mathematical questions (e.g. how many trees do yousee in this scene?). In some embodiments, the questions becomeprogressively more difficult as the user answers correctly. In someembodiments, the information acquired when taking pictures is organizedin a report format. For example, if a student is supposed to do a reporton different types of trees, and the student takes pictures of 5different trees, a report, including the pictures, is generated withdetails about the trees. In some embodiments, the user is able to take apicture of a food item, and recipes are generated that use that item. Insome embodiments, the user is able to take a picture of a store (e.g.restaurant), and information about that store is presented including,but not limited to, user ratings/reviews, critic ratings/reviews, hoursof operation, menu and/or a description of the store. In someembodiments, the user does not have to take a picture; rather, the usermerely points the lens of the camera of the mobile device at the object,and the device is able to scan the object. The information providedabout the object is able to be based on a database lookup, a search orany other implementation. In some embodiments, the user takes a pictureor points the camera at a street sign, and a list of items (e.g.restaurants) is displayed in order of proximity, ratings and/or reviews,for example. In some embodiments, GPS or another locating mechanism isused for determining a user's location.

In some embodiments, users are given rewards, awards and/or prizes forparticipating with and/or contributing to the fact checker.

In some embodiments, a collection of incorrect predictions and/orstatements and/or hypocrisy is maintained.

In some embodiments, a shortcut fact checker is implemented. Theshortcut fact checker performs a shortcut fact check and indicates“likely true,” “likely false” or another indication. The shortcut factcheck is implemented by performing a search and based on the number ofresults, indicating “likely true” or “likely false.” For example, if asearch results in zero results or few results, “likely false” isindicated. If a search results in many results, “likely true” isindicated. In some embodiments, the shortcut fact checker usesreliability ratings to narrow sources used. In some embodiments, theresult accuracy rating is used (e.g. only “likely true” if there aremany results with an accuracy rating above a threshold).

In some embodiments, the fact checker is implemented to correct wordpronunciation of any communication (e.g. of broadcast information). Forexample, people's names, geographic locations and any other words areable to be corrected. In some embodiments, the fact checker compares thesound clip with another sound clip. For example, a database of people'snames is stored and when their name is spoken, the pronunciation iscompared with the stored data in the database. For example, each playeron a football team says his name, and it is recorded in a database,then, when a broadcaster says his name, if it is mispronounced, someform of action is taken including, but not limited to, playing thecorrect version to the user, playing the correct version to thebroadcaster so that he is able to repeat it, playing a chime to thebroadcaster, displaying a phonetic spelling to the users and/or thebroadcaster, and/or any other indication. In some embodiments, the soundclip is converted into text, and then the text is compared with apronunciation guide. In some embodiments, the fact checker isimplemented to correct grammar of any communication (e.g. of broadcastinformation). For example, if a commentator says, “I'm doing good,” thegrammar correction is able to correct the statement by indicating, “I'mdoing well.” The indication is able to be any indication; for example,sending a corrective Tweet to a user's mobile device.

In some embodiments, a lie detector is implemented with the factchecker. The lie detector analyzes a speaker's voice, body language,heart rate and/or any other information to determine if the person istelling the truth. For example, a video of a speaker is analyzed inconjunction with fact checking the content of the communication toprovide a better assessment of the video. The lie detection analysis isable to be used to provide context to the fact checking analysis or viceversa.

In some embodiments, tracking is implemented. For example, words and/orphrases are tracked as a speech is displayed, throughout the speech orat the end of the speech, the number of repeats is displayed. Forexample, if the President says, “job creation” 5 times in a speech, thattotal is presented to the viewer. The information is also able to usedfor analysis of the speech (e.g. automatically determining the focus ofthe speech). In another example, words and/or phrases are tracked, andsupplemental information is presented related to the trackedinformation. For example, if the President says, we need to “increaseour energy independence,” supplemental information is able to be shownto the viewer that the past 5 presidents have said the same or similaridea, and the viewer is able to understand that this may be a point withlittle substance. The phrases do not have to be verbatim matches;similar matches are able to be found.

In some embodiments, fact check information and/or supplementalinformation is displayed on a mobile device while the user is talking onthe phone. For example, both sides of a user's phone conversation arebeing fact checked, and if something is detected as untrue, the factchecker indicates it to the user.

In some embodiments, user information is acquired to be used by the factchecker and/or supplemental information, for example, for advertising.

In some embodiments, information is presented in real-time, but alsosaved/stored so that the user is able to review the information later.The information is searchable, able to be categorized and/ororganized/formatted in any manner.

In some embodiments, the date/time of a comment is recorded and/ordetermined. For example, if one entity begins a trend by saying a catchyphrase, and then other entities repeat the phrase making it out to betheir original idea, a note is able to be presented giving credit to thefirst entity. Comparisons of dates/times or other implementations areable to be used in determining the first entity versus subsequententities.

In some embodiments, the fact checker is able to detect changed names.For example, high fructose corn syrup is being changed to corn sugar. Bydetecting changed names, either name is able to be used in the factcheck or to provide supplemental information. For example, if a personmakes a comment about “corn sugar,” the fact checker knows to search for“corn sugar” as well as “high fructose corn syrup.” The implementationcould be by using a database which stores name changes and searchesbased on all known names, or by using an embedded search to search forother names, or any other implementation.

In some embodiments, artificial intelligence is used in any aspect ofthe methods and systems described herein. For example, artificialintelligence is used to determine which follow-up question to ask aguest on a television show.

In some embodiments, the fact checker is used with teleprompters and/orto fact check scripts prior to airing. In some embodiments, the factchecker implements measures to prevent hacking, skewing and/or othertampering of the system.

In some embodiments, the fact checker is linked to or is a part of agaming system.

In some embodiments, an independent fact checker device is implementedwhere the device receives information (e.g. a television signal) withoutthe television being on and is able to perform monitoring, searching,analysis, and/or any other tasks.

In some embodiments, one or more of the data structures described hereinare populated automatically, (e.g. by automatically searching andstoring results in the data structure), manually, or a combinationthereof.

In some embodiments, a scam checker is implemented using the factchecker. In some embodiments, the scam checker checks websites and/oremails to determine if they are safe. In some embodiments, the scamchecker determines if an advertisement is a scam (dishonest scheme orfraud). In some embodiments, a scam is detected using a database ofscams. For example, content (e.g. of a website) is compared withlanguage in a database. In some embodiments, a scam is detected bydetermining it is similar to other scams. In some embodiments, a scam isdetected by determining it is mathematically or economically impossible.In some embodiments, a scam is detected by determining the contentincludes misinformation. In some embodiments, a scam is detected bysearching other website and/or weblogs that have commented on the scam.In some embodiments, a user is able to request a website to be factchecked by inputting a URL in a user interface of the fact checker. Anyimplementation is able to be used to detect a scam. In some embodiments,a scam website is indicated as such when displayed in a search engineresult or other webpage (e.g. bubble when mouse over link).

Medical

In some embodiments, a medical fact checker is implemented. The medicalfact checker monitors, processes, fact checks and indicates information.In some embodiments, the fact checker checks the information with alimited set of sources (e.g. validated medical sources). For example, insome embodiments, only medical journals and studies are used as sourcesfor fact checking. In some embodiments, other sources are used, but thesources are still certified as valid before being used. In someembodiments, additional sources are used such as medical websites. Insome embodiments, a designated medical database is used as a source. Forexample, a database of all known illnesses and symptoms is utilized as asource. In some embodiments, users are able to specify their thresholdfor sources to use. The medical fact checker is able to be utilized invarious implementations. In some embodiments, a user inputs (e.g. saysor types), “I think I have X disease, because I have symptoms A, B, andC.” The medical fact checker fact checks the statement by looking up thedisease and symptoms for the disease to see if the symptoms match thedisease. In some embodiments, statistics are determined and indicated tothe user. In some embodiments, additional information about the personis utilized to assist in performing the medical fact check, including,but not limited to, age, weight, height, race, previous conditions, timeof the year, location, genetic conditions, family history, vaccinations,recent activities, recent travels, and any other information. Forexample, if the user says, “I think I have Polio because I have a feverand a headache,” the medical fact checker indicates a 0.0001% chance ofPolio based on recent diagnosis rates and/or any other data. In someembodiments, the medical fact checker indicates possibleillnesses/conditions based on the symptom(s). For example, a list ofpossible illnesses/conditions is presented. In some embodiments,information is displayed to indicate that the listedillnesses/conditions include some symptoms described but not others.

In some embodiments, the medical fact checker prevents misinformationfrom being spread by fact checking email, websites, broadcastinformation and any other information. The fact checker compares theinformation with medical journals and/or other medical information todetermine the validity of the information. For example, an emaildiscussing homeopathic remedies is fact checked and/or to providesupplemental information about the remedies (e.g. what plant the remedycomes from, where it is located, any tests or studies done with theremedy, if the remedy is FDA approved, and other information). Forfurther example, medical analysis is presented regarding the remedy. Insome embodiments, it is determined if the medical information is staleand/or if a newer study has been performed. In some embodiments,information about the source of the information is fact checked and/orsupplemental information presented. For example, the doctor'scredentials are displayed (and fact checked), the medical school'sinformation is displayed, certifications are fact checked and displayed,study information is displayed, any criminal charges, complaints and/orcomments are displayed and/or any other information is displayed. Insome embodiments, a database is implemented to trackdeceptive/false/fake medicine, doctors and/or medical information. Insome embodiments, an email, website and/or other content is analyzed todetermine if an item is being sold. For example, an email is distributedabout being tired, and at the end of the email is an item to curetiredness. The sales pitch is highlighted or indicated in a manner toalert the user of possible misinformation or medical scam.

In some embodiments, the fact checker checks for allergy information ofitems. For example, a device acquires allergy information by scanningthe ingredients label, taking a picture of the ingredients label, usinga barcode reader to determine the ingredients information, using RFIDinformation, and/or any method of determining the ingredients and/orfood preparation information (including, but not limited to, “processedin a plant that also processes X”). The fact checker then compares theinformation to a database of allergy information. In some embodiments,the fact checker uses a higher level approach and fact checks theallergy information by the name of the item. Any other implementation offact checking the item for allergy information is able to be used toassist a user in avoiding allergic reactions, such as postings on awebsite or statements a company has made about a product in a FAQ, blog,or other location. Analysis such as fact checking is able to be done todetermine the reliability of the posting; for example, a bloggerreceives a reliability or credibility rating.

Utilizing the fact checking system, method and device depends on theimplementation to some extent. In some implementations, a word processoruses fact checking to assist a user in preparing a document, atelevision broadcast uses fact checking to fact check what is said orshown to the viewers, and a mobile application, in some embodiments,uses fact checking to ensure a user provides factually correctinformation. The fact checking is able to be implemented without userintervention. For example, if a user is watching a news program, thefact checking is able to automatically occur and present the appropriateinformation. In some embodiments, users are able to disable the factchecking if desired. Similarly, if a user implements fact checking onhis word processor or mobile application, the fact checking occursautomatically. For a news company, the fact checking is also able to beimplemented automatically, so that once installed and/or configured, thenews company does not need take any additional steps to utilize the factchecking. In some embodiments, the news company is able to takeadditional steps such as adding sources. In some embodiments, newscompanies are able to disable the fact checking, and in someembodiments, news companies are not able to disable the fact checking toavoid tampering and manipulation of data. In some embodiments, one ormore aspects of the fact checking are performed manually.

In operation, the fact checking system, method and device enableinformation to be fact checked in real-time and automatically (e.g.without user intervention). The monitoring, processing, fact checkingand indicating of status are each able to occur automatically, withoutuser intervention. Results of the fact checking are able to be presentednearly instantaneously, so that viewers of the information are able tobe sure they are receiving accurate and truthful information.Additionally, the fact checking is able to clarify meaning, tone,context and/or other elements of a comment to assist a user or viewer.By utilizing the speed and breadth of knowledge that comes withautomatic, computational fact checking, the shortcomings of human factchecking are greatly overcome. With instantaneous or nearlyinstantaneous fact checking, viewers will not be confused as to whatinformation is being fact checked since the results are postedinstantaneously or nearly instantaneously versus when a fact check isperformed by humans and the results are posted minutes later. The rapidfact checking provides a significant advantage over past data analysisimplementations. Any of the steps described herein are able to beimplemented automatically.

Examples of Implementation Configurations:

Although the monitoring, processing, fact checking and indicating areable to occur on any device and in any configuration, these are somespecific examples of implementation configurations. Monitoring,processing, fact checking and indicating all occur on a broadcaster'sdevices (or other emitters of information including, but not limited to,news stations, radio stations and newspapers). Monitoring, processingand fact checking occur on a broadcaster's devices, and indicatingoccurs on an end-user's device. Monitoring and processing occur on abroadcaster's devices, fact checking occurs on a broadcaster's devicesin conjunction with third-party devices, and indicating occurs on anend-user's device. Monitoring occurs on a broadcaster's devices,processing and indicating occur on an end-user's device, and factchecking occurs on third-party devices. Monitoring, processing, factchecking, and indicating all occur on third-party devices. Monitoring,processing, fact checking, and indicating all occur on an end-user'sdevice. These are only some examples; other implementations arepossible. Additionally, supplemental information is able to be monitoredfor, searched for, processed and/or indicated using any of theimplementations described herein.

Fact checking includes checking the factual accuracy and/or correctnessof information. The type of fact checking is able to be any form of factchecking such as checking historical correctness/accuracy, grammaticalcorrectness/accuracy, geographical correctness/accuracy, mathematicalcorrectness/accuracy, scientific correctness/accuracy, literarycorrectness/accuracy, objective correctness/accuracy, subjectivecorrectness/accuracy, and/or any other correctness/accuracy. Another wayof viewing fact checking includes determining the correctness of astatement of objective reality or an assertion of objective reality. Yetanother way of viewing fact checking includes determining whether astatement, segment or phrase is true or false.

Although some implementations and/or embodiments have been describedrelated to specific implementations and/or embodiments, and someaspects/elements/steps of some implementations and/or embodiments havebeen described related to specific implementations and/or embodiments,any of the aspects/elements/steps, implementations and/or embodimentsare applicable to other aspects/elements/steps, implementations and/orembodiments described herein.

The present invention has been described in terms of specificembodiments incorporating details to facilitate the understanding ofprinciples of construction and operation of the invention. Suchreference herein to specific embodiments and details thereof is notintended to limit the scope of the claims appended hereto. It will bereadily apparent to one skilled in the art that other variousmodifications may be made in the embodiment chosen for illustrationwithout departing from the spirit and scope of the invention as definedby the claims.

What is claimed is:
 1. A method programmed in a non-transitory memory ofa device comprising: a. automatically monitoring social media content;b. automatically fact checking the social media content with the deviceby comparing the social media content with source information todetermine the factual accuracy of the social media content; c.automatically indicating a status of the social media content inreal-time based on a result of the comparison of the social mediacontent with the source information; and d. detecting bias of the socialmedia content wherein a data structure stores biased information andbiased entities to be used for determining the bias.
 2. The method ofclaim 1 further comprising automatically processing the social mediacontent including parsing the social media content into fact checkableportions.
 3. The method of claim 1 wherein fact checking utilizes aplurality of sources, and each source of the plurality of sources has areliability rating based on the accuracy of the information within eachsource of the plurality of sources, wherein the accuracy is determinedbased on previous fact checking results, wherein a first source with afirst reliability rating is given more weight during fact checking thana second source with a second reliability rating lower than the firstreliability rating, wherein each source of the plurality of sources withthe reliability rating below a threshold is not used in fact checking.4. The method of claim 3 wherein the threshold is a user-specifiedthreshold.
 5. The method of claim 3 wherein the reliability rating isgenerated using a combination of user-generated ratings andcomputer-generated ratings.
 6. The method of claim 1 further comprisingindicating supplemental information including an importance ratingindicating an importance of the social media content to a user whereinthe importance rating is determined by: i. classifying the social mediacontent into a classification; ii. comparing the classification with animportance selection; and iii. generating the importance rating based onthe comparison of the classification and the importance selection. 7.The method of claim 1 wherein fact checking includes analyzing causationwithin the social media content, further wherein the causation isdetermined by logical flaws within the social media content.
 8. Themethod of claim 1 further comprising displaying an advertisement basedon the social media content.
 9. The method of claim 1 further comprisingdisplaying an advertisement opposing the social media content.
 10. Themethod of claim 1 further comprising automatically sending the result toa second device.
 11. The method of claim 1 wherein the sourceinformation is ranked by popularity, and fact checking utilizes a mostpopular source information first and less popular source information ina descending order.
 12. The method of claim 1 wherein fact checking isperformed using cloud computing.
 13. The method of claim 1 furthercomprising classifying the social media content in a politicalclassification.
 14. The method of claim 1 wherein the social mediacontent comprises a subjective statement, and fact checking thesubjective statement includes comparing the subjective statement withthe source information including comparing objective information relatedto the subjective statement with the source information to generate theresult.
 15. The method of claim 1 further comprising receiving flagginginformation, wherein fact checking includes fact checking a flaggedsocial media content.
 16. The method of claim 1 wherein fact checkingutilizes previously stored fact check results.
 17. The method of claim 1wherein sources of the source information are clustered to enableselecting of a cluster of sources to be used for fact checking.
 18. Amethod programmed in a non-transitory memory of a device comprising: a.automatically monitoring social media content with the device; b.automatically indicating a status of the social media content inreal-time based on a result of a fact checking comparison of the socialmedia content with source information to determine the factual accuracyof the social media content; and c. displaying an advertisement opposingthe social media content.
 19. A device comprising: a. a memory forstoring an application for automatically performing the following steps:i. monitoring social media content; ii. processing the social mediacontent including parsing the social media content into fact checkableportions; iii. fact checking the fact checkable portions by comparingthe fact checkable portions with source information to determine thefactual accuracy of the fact checkable portions, wherein the socialmedia content comprises a subjective statement, and fact checking thesubjective statement includes comparing the subjective statement withthe source information including comparing objective information relatedto the subjective statement with the source information to generate aresult; and iv. indicating a status of the social media content inreal-time based on the result of the comparison of the fact checkableportions with the source information; and b. a processor for processingthe application.
 20. A method programmed in a non-transitory memory of adevice comprising: a. automatically monitoring social media content; b.receiving flagging information; c. automatically fact checking thesocial media content with the device by comparing the social mediacontent with source information to determine the factual accuracy of thesocial media content, wherein fact checking includes fact checkingflagged social media content; d. automatically indicating a status ofthe social media content in real-time based on a result of thecomparison of the social media content with the source information; ande. detecting bias of the social media content wherein a data structurestores biased information and biased entities to be used for determiningthe bias.